From 5e7e20c704b8ae63991c6d89745620e3521b1688 Mon Sep 17 00:00:00 2001 From: ivan-digital Date: Sat, 4 Jul 2026 10:02:51 +0200 Subject: [PATCH 1/6] Use TTS capability descriptors --- src-tauri/src/lib.rs | 219 ++++++++++++++++++++++++++- src/components/ScriptEditor.test.tsx | 78 +++++++++- src/components/ScriptEditor.tsx | 75 +++++---- src/components/TopBar.tsx | 41 +++-- src/i18n/messages.ts | 4 + src/ipc/commands.ts | 21 ++- src/state/projectStore.test.ts | 55 +++++++ src/state/projectStore.ts | 34 +++-- src/types/project.ts | 6 +- 9 files changed, 470 insertions(+), 63 deletions(-) diff --git a/src-tauri/src/lib.rs b/src-tauri/src/lib.rs index a526d43..04babf1 100644 --- a/src-tauri/src/lib.rs +++ b/src-tauri/src/lib.rs @@ -407,10 +407,70 @@ impl TtsEngine { } } + fn model_name(self) -> &'static str { + match self { + Self::VoxCPM2 => "voxcpm2-mlx-int8", + Self::CosyVoice => "cosyvoice-3-0.5b-mlx-bf16", + Self::Qwen3 => "qwen3-tts-1.7b-mlx-bf16", + Self::Chatterbox => "chatterbox-multilingual-mlx-fp16", + Self::OmniVoice => "omnivoice-mlx-int8", + Self::IndicMio => "indic-mio-mlx-fp16", + Self::FishAudio => "fish-audio-s2-pro-mlx-fp16", + } + } + + fn model_id(self) -> &'static str { + match self { + Self::VoxCPM2 => "aufklarer/VoxCPM2-MLX-int8", + Self::CosyVoice => "aufklarer/CosyVoice3-0.5B-MLX-bf16", + Self::Qwen3 => "aufklarer/Qwen3-TTS-12Hz-1.7B-Base-MLX-bf16", + Self::Chatterbox => "aufklarer/Chatterbox-Multilingual-MLX-fp16", + Self::OmniVoice => "aufklarer/OmniVoice-MLX-int8", + Self::IndicMio => "aufklarer/Indic-Mio-MLX-fp16", + Self::FishAudio => "aufklarer/Fish-Audio-S2-Pro-MLX-fp16", + } + } + + fn model_size(self) -> &'static str { + match self { + Self::CosyVoice => "0.5B", + Self::Qwen3 => "1.7B", + Self::Chatterbox => "0.5B", + Self::OmniVoice => "0.5B", + Self::IndicMio => "0.6B", + Self::VoxCPM2 => "1.7B", + Self::FishAudio => "S2 Pro", + } + } + + fn languages(self) -> &'static [&'static str] { + match self { + Self::Qwen3 => &["zh", "en", "ja", "ko", "de", "fr", "ru", "pt", "es", "it"], + Self::Chatterbox => &[ + "ar", "da", "de", "el", "en", "es", "fi", "fr", "he", "hi", "it", "ja", "ko", "ms", + "nl", "no", "pl", "pt", "ru", "sv", "sw", "tr", "zh", + ], + Self::OmniVoice => &[ + "en", "hi", "ru", "es", "fr", "de", "it", "pt", "zh", "ja", "ko", + ], + Self::IndicMio => &["hi", "en"], + Self::FishAudio => &["hi", "en"], + Self::VoxCPM2 | Self::CosyVoice => &["en", "zh"], + } + } + + fn voice_profile_modes(self) -> &'static [&'static str] { + &["reference-clone"] + } + fn requires_reference_transcript(self) -> bool { matches!(self, Self::CosyVoice | Self::Qwen3 | Self::FishAudio) } + fn requires_reference_audio(self) -> bool { + true + } + /// Whether synthesis needs a caller-chosen language. Chatterbox prepends a /// `[lang]` token, so the Studio shows a language picker for it; the other /// engines infer language from the text. @@ -420,6 +480,7 @@ impl TtsEngine { /// How the engine applies inline emotion markers — drives the editor hint: /// - `instruction`: marker → an engine-specific style instruction. + /// - `controlled-vocabulary`: marker → fixed engine vocabulary only. /// - `intensity`: marker → an expressiveness level only (Chatterbox; not a /// specific emotion). /// - `suffix-tag`: marker is appended as an engine-specific suffix tag. @@ -427,13 +488,105 @@ impl TtsEngine { /// - `none`: markers are stripped and ignored. fn style_mode(self) -> &'static str { match self { - Self::VoxCPM2 | Self::CosyVoice | Self::OmniVoice => "instruction", + Self::VoxCPM2 | Self::CosyVoice => "instruction", + Self::OmniVoice => "controlled-vocabulary", Self::Chatterbox => "intensity", Self::IndicMio => "suffix-tag", Self::FishAudio => "bracket-tag", Self::Qwen3 => "none", } } + + fn supports_instruct(self) -> bool { + matches!(self, Self::VoxCPM2 | Self::CosyVoice) + } + + fn supported_markers(self) -> &'static [&'static str] { + match self { + Self::VoxCPM2 | Self::CosyVoice => &[ + "soft", + "warm", + "whispering", + "intense", + "excited", + "happy", + "calm", + "serious", + "surprised", + "sad", + "angry", + "dramatic", + "laughs", + ], + Self::OmniVoice => &[ + "whispering", + "excited", + "happy", + "calm", + "serious", + "sad", + "angry", + ], + Self::Chatterbox => &[ + "soft", + "warm", + "whispering", + "intense", + "excited", + "happy", + "calm", + "serious", + "surprised", + "sad", + "angry", + "dramatic", + "laughs", + ], + Self::IndicMio => &["happy", "sad", "angry", "disgust", "fear", "surprise"], + Self::FishAudio => &[ + "pause", + "emphasis", + "laughing", + "excited", + "angry", + "whisper", + "screaming", + "shouting", + "surprised", + "sad", + ], + Self::Qwen3 => &[], + } + } + + fn needs_trim(self) -> bool { + trim_long_form_chunk_edges(self) + } + + fn sample_rate(self) -> u32 { + match self { + Self::VoxCPM2 => 48_000, + Self::FishAudio => 44_100, + Self::CosyVoice | Self::Qwen3 | Self::Chatterbox | Self::OmniVoice | Self::IndicMio => { + 24_000 + } + } + } + + fn use_policy(self) -> &'static str { + match self { + Self::FishAudio => "research-only", + _ => "commercial-safe", + } + } + + fn readiness(self) -> &'static str { + match self { + Self::Qwen3 => "legacy-fallback", + Self::FishAudio => "benchmark", + _ => "production", + } + } } fn normalize_sidecar_language(engine: TtsEngine, language: Option<&str>) -> Option { @@ -441,12 +594,12 @@ fn normalize_sidecar_language(engine: TtsEngine, language: Option<&str>) -> Opti match engine { // The UI keeps BCP-47-ish ids because Chatterbox expects `[hi]`, but // OmniVoice gives cleaner Hindi output with the spelled language item. - TtsEngine::OmniVoice | TtsEngine::IndicMio => trimmed.map(|value| { - match value.to_ascii_lowercase().as_str() { + TtsEngine::OmniVoice | TtsEngine::IndicMio => { + trimmed.map(|value| match value.to_ascii_lowercase().as_str() { "hi" | "hin" => "hindi".to_string(), _ => value.to_string(), - } - }), + }) + } _ => trimmed.map(str::to_string), } } @@ -502,21 +655,55 @@ struct TtsEngineInfo { id: TtsEngine, #[serde(rename = "displayName")] display_name: &'static str, + #[serde(rename = "modelName")] + model_name: &'static str, + #[serde(rename = "modelId")] + model_id: &'static str, + #[serde(rename = "modelSize")] + model_size: &'static str, + languages: &'static [&'static str], + #[serde(rename = "voiceProfileModes")] + voice_profile_modes: &'static [&'static str], + #[serde(rename = "requiresReferenceAudio")] + requires_reference_audio: bool, #[serde(rename = "requiresReferenceTranscript")] requires_reference_transcript: bool, #[serde(rename = "requiresLanguage")] requires_language: bool, #[serde(rename = "styleMode")] style_mode: &'static str, + #[serde(rename = "supportsInstruct")] + supports_instruct: bool, + #[serde(rename = "supportedMarkers")] + supported_markers: &'static [&'static str], + #[serde(rename = "needsTrim")] + needs_trim: bool, + #[serde(rename = "sampleRate")] + sample_rate: u32, + #[serde(rename = "usePolicy")] + use_policy: &'static str, + readiness: &'static str, } fn tts_engine_info(engine: TtsEngine) -> TtsEngineInfo { TtsEngineInfo { id: engine, display_name: engine.display_name(), + model_name: engine.model_name(), + model_id: engine.model_id(), + model_size: engine.model_size(), + languages: engine.languages(), + voice_profile_modes: engine.voice_profile_modes(), + requires_reference_audio: engine.requires_reference_audio(), requires_reference_transcript: engine.requires_reference_transcript(), requires_language: engine.requires_language(), style_mode: engine.style_mode(), + supports_instruct: engine.supports_instruct(), + supported_markers: engine.supported_markers(), + needs_trim: engine.needs_trim(), + sample_rate: engine.sample_rate(), + use_policy: engine.use_policy(), + readiness: engine.readiness(), } } @@ -2917,9 +3104,31 @@ mod tests { assert_eq!(TtsEngine::VoxCPM2.style_mode(), "instruction"); assert_eq!(TtsEngine::IndicMio.style_mode(), "suffix-tag"); assert_eq!(TtsEngine::FishAudio.style_mode(), "bracket-tag"); + assert_eq!(TtsEngine::OmniVoice.style_mode(), "controlled-vocabulary"); assert_eq!(TtsEngine::Qwen3.style_mode(), "none"); } + #[test] + fn tts_engine_info_exposes_model_capabilities() { + let qwen = tts_engine_info(TtsEngine::Qwen3); + assert_eq!(qwen.model_name, "qwen3-tts-1.7b-mlx-bf16"); + assert_eq!(qwen.model_id, "aufklarer/Qwen3-TTS-12Hz-1.7B-Base-MLX-bf16"); + assert_eq!(qwen.voice_profile_modes, &["reference-clone"]); + assert!(qwen.requires_reference_audio); + assert!(qwen.requires_reference_transcript); + assert!(!qwen.supports_instruct); + assert_eq!(qwen.style_mode, "none"); + assert!(qwen.languages.contains(&"en")); + assert!(qwen.languages.contains(&"ru")); + assert!(qwen.supported_markers.is_empty()); + + let fish = tts_engine_info(TtsEngine::FishAudio); + assert_eq!(fish.style_mode, "bracket-tag"); + assert!(fish.supported_markers.contains(&"excited")); + assert_eq!(fish.use_policy, "research-only"); + assert!(!fish.needs_trim); + } + #[test] fn sidecar_language_normalization_preserves_chatterbox_hi() { assert_eq!( diff --git a/src/components/ScriptEditor.test.tsx b/src/components/ScriptEditor.test.tsx index 07244be..c886c4e 100644 --- a/src/components/ScriptEditor.test.tsx +++ b/src/components/ScriptEditor.test.tsx @@ -3,6 +3,28 @@ import { fireEvent, render, screen } from "@testing-library/react"; import { ScriptEditor } from "./ScriptEditor"; import { EMOTION_TAGS } from "../types/project"; import { useProjectStore } from "../state/projectStore"; +import type { TtsEngineInfo } from "../ipc/commands"; + +function engineInfo(patch: Partial & Pick): TtsEngineInfo { + return { + modelName: patch.id, + modelId: `test/${patch.id}`, + modelSize: "test", + languages: ["en"], + voiceProfileModes: ["reference-clone"], + requiresReferenceAudio: true, + requiresReferenceTranscript: false, + requiresLanguage: false, + styleMode: "instruction", + supportsInstruct: true, + supportedMarkers: [...EMOTION_TAGS], + needsTrim: true, + sampleRate: 24_000, + usePolicy: "commercial-safe", + readiness: "production", + ...patch, + }; +} describe("ScriptEditor", () => { beforeEach(() => { @@ -55,13 +77,15 @@ describe("ScriptEditor", () => { engine: "indic-mio", language: "hi", engines: [ - { + engineInfo({ id: "indic-mio", displayName: "Indic-Mio", requiresReferenceTranscript: false, requiresLanguage: false, styleMode: "suffix-tag", - }, + supportsInstruct: false, + supportedMarkers: ["happy", "sad", "angry"], + }), ], status: "ready", }, @@ -78,13 +102,15 @@ describe("ScriptEditor", () => { engine: "fish-audio", language: "en", engines: [ - { + engineInfo({ id: "fish-audio", displayName: "Fish Audio S2 Pro", requiresReferenceTranscript: true, requiresLanguage: false, styleMode: "bracket-tag", - }, + supportsInstruct: false, + supportedMarkers: ["sad", "excited"], + }), ], status: "ready", }, @@ -94,4 +120,48 @@ describe("ScriptEditor", () => { fireEvent.click(screen.getByRole("button", { name: "excited" })); expect(onChange).toHaveBeenCalledWith("[excited] नमस्ते"); }); + + it("uses the engine-provided marker palette", () => { + useProjectStore.setState({ + model: { + engine: "fish-audio", + language: "en", + engines: [ + engineInfo({ + id: "fish-audio", + displayName: "Fish Audio S2 Pro", + styleMode: "bracket-tag", + supportedMarkers: ["whisper", "excited"], + }), + ], + status: "ready", + }, + }); + render( {}} />); + expect(screen.getAllByRole("button").map((button) => button.textContent)).toEqual([ + "whisper", + "excited", + ]); + }); + + it("does not render marker buttons when the active engine ignores markers", () => { + useProjectStore.setState({ + model: { + engine: "qwen3", + language: "en", + engines: [ + engineInfo({ + id: "qwen3", + displayName: "Qwen3-TTS", + styleMode: "none", + supportsInstruct: false, + supportedMarkers: [], + }), + ], + status: "ready", + }, + }); + render( {}} />); + expect(screen.queryAllByRole("button")).toHaveLength(0); + }); }); diff --git a/src/components/ScriptEditor.tsx b/src/components/ScriptEditor.tsx index 545f15c..d49f13b 100644 --- a/src/components/ScriptEditor.tsx +++ b/src/components/ScriptEditor.tsx @@ -1,5 +1,5 @@ import { useRef } from "react"; -import { EMOTION_TAGS, EmotionTag } from "../types/project"; +import { EMOTION_TAGS } from "../types/project"; import { useProjectStore } from "../state/projectStore"; import { Textarea } from "./ui/textarea"; import { Button } from "./ui/button"; @@ -10,20 +10,6 @@ interface ScriptEditorProps { onChange: (value: string) => void; } -const INDIC_MIO_TAGS = ["happy", "sad", "angry", "disgust", "fear", "surprise"] as const; -const FISH_AUDIO_TAGS = [ - "pause", - "emphasis", - "laughing", - "excited", - "angry", - "whisper", - "screaming", - "shouting", - "surprised", - "sad", -] as const; - // Match `(tag)` or `...` wrappers at the start of a line so we can // swap them out cleanly. Permissive on tag character set to allow custom // emotion descriptors like `(slow and dreamy)`. @@ -46,16 +32,43 @@ function stripEmotionTag(text: string): string { return out.replace(TRAILING_XML_SUFFIX, "").replace(TRAILING_BRACKET_SUFFIX, ""); } +function rawMarkerValue(marker: string): string { + const value = marker.trim(); + if ( + (value.startsWith("<") && value.endsWith(">")) || + (value.startsWith("[") && value.endsWith("]")) || + (value.startsWith("(") && value.endsWith(")")) + ) { + return value.slice(1, -1).trim().toLowerCase(); + } + return value.toLowerCase(); +} + +function suffixMarker(marker: string): string { + const value = marker.trim(); + return value.startsWith("<") && value.endsWith(">") ? value : `<${value}>`; +} + +function bracketMarker(marker: string): string { + const value = marker.trim(); + return value.startsWith("[") && value.endsWith("]") ? value : `[${value}]`; +} + export function ScriptEditor({ value, onChange }: ScriptEditorProps) { const { messages: m } = useI18n(); const ref = useRef(null); - const styleMode = useProjectStore( - (s) => s.model.engines.find((e) => e.id === s.model.engine)?.styleMode ?? "instruction", + const engineInfo = useProjectStore( + (s) => s.model.engines.find((e) => e.id === s.model.engine), ); + const styleMode = engineInfo?.styleMode ?? "instruction"; const markersIgnored = styleMode === "none"; const suffixMode = styleMode === "suffix-tag"; const bracketMode = styleMode === "bracket-tag"; - const markerTags = suffixMode ? INDIC_MIO_TAGS : bracketMode ? FISH_AUDIO_TAGS : EMOTION_TAGS; + const markerTags = markersIgnored + ? [] + : engineInfo?.supportedMarkers.length + ? engineInfo.supportedMarkers + : [...EMOTION_TAGS]; const rawCurrentTag = suffixMode ? value.match(TRAILING_XML_SUFFIX)?.[1] : bracketMode @@ -65,6 +78,8 @@ export function ScriptEditor({ value, onChange }: ScriptEditorProps) { const styleHint = styleMode === "intensity" ? m.script.styleHints.intensity + : styleMode === "controlled-vocabulary" + ? m.script.styleHints.controlledVocabulary : styleMode === "suffix-tag" ? m.script.styleHints.suffixTag : styleMode === "bracket-tag" @@ -73,19 +88,18 @@ export function ScriptEditor({ value, onChange }: ScriptEditorProps) { ? m.script.styleHints.none : m.script.styleHints.instruction; - function applyTag( - tag: EmotionTag | (typeof INDIC_MIO_TAGS)[number] | (typeof FISH_AUDIO_TAGS)[number], - ) { + function applyTag(tag: string) { const body = stripEmotionTag(value).trim(); - if (currentTag === tag) { + const rawTag = rawMarkerValue(tag); + if (currentTag === rawTag) { // Toggle off: clicking the active tag removes it. onChange(body); } else if (suffixMode) { - onChange(`${body} <${tag}>`.trim()); + onChange(`${body} ${suffixMarker(tag)}`.trim()); } else if (bracketMode) { - onChange(`[${tag}] ${body}`.trim()); + onChange(`${bracketMarker(tag)} ${body}`.trim()); } else { - onChange(`(${tag}) ${body}`); + onChange(`(${rawTag}) ${body}`); } requestAnimationFrame(() => ref.current?.focus()); } @@ -104,8 +118,13 @@ export function ScriptEditor({ value, onChange }: ScriptEditorProps) { />
{markerTags.map((tag) => { - const active = currentTag === tag; - const markerLabel = suffixMode ? `<${tag}>` : bracketMode ? `[${tag}]` : `(${tag})`; + const rawTag = rawMarkerValue(tag); + const active = currentTag === rawTag; + const markerLabel = suffixMode + ? suffixMarker(tag) + : bracketMode + ? bracketMarker(tag) + : `(${rawTag})`; return ( ); })} diff --git a/src/components/TopBar.tsx b/src/components/TopBar.tsx index 63c5b96..f6fabed 100644 --- a/src/components/TopBar.tsx +++ b/src/components/TopBar.tsx @@ -142,17 +142,31 @@ function ModelChip({ ); } -/** Languages a per-language engine (Chatterbox) can synthesize today. */ -const TTS_LANGUAGES: { id: string; label: string }[] = [ - { id: "en", label: "English" }, - { id: "ar", label: "العربية" }, - { id: "hi", label: "हिन्दी" }, - { id: "de", label: "Deutsch" }, - { id: "es", label: "Español" }, - { id: "fr", label: "Français" }, - { id: "it", label: "Italiano" }, - { id: "pt", label: "Português" }, -]; +const TTS_LANGUAGE_LABELS: Record = { + ar: "العربية", + da: "Dansk", + de: "Deutsch", + el: "Ελληνικά", + en: "English", + es: "Español", + fi: "Suomi", + fr: "Français", + he: "עברית", + hi: "हिन्दी", + it: "Italiano", + ja: "日本語", + ko: "한국어", + ms: "Bahasa Melayu", + nl: "Nederlands", + no: "Norsk", + pl: "Polski", + pt: "Português", + ru: "Русский", + sv: "Svenska", + sw: "Kiswahili", + tr: "Türkçe", + zh: "中文", +}; export function TopBar() { const { locale, messages: t } = useI18n(); @@ -177,6 +191,9 @@ export function TopBar() { const modelStatus = model.status; const engineInfo = model.engines.find((candidate) => candidate.id === model.engine); const engineName = engineInfo?.displayName ?? "VoxCPM2"; + const languageOptions = (engineInfo?.languages.length ? engineInfo.languages : ["en"]).map( + (id) => ({ id, label: TTS_LANGUAGE_LABELS[id] ?? id }), + ); const synthDisabled = synthBusy || modelStatus !== "ready" || !hasContent; const engineSwitchDisabled = synthBusy; const synthMode: "missing" | "all" = missingCount > 0 ? "missing" : "all"; @@ -345,7 +362,7 @@ export function TopBar() { - {TTS_LANGUAGES.map((lang) => ( + {languageOptions.map((lang) => ( {lang.label} diff --git a/src/i18n/messages.ts b/src/i18n/messages.ts index 51697c3..08b6673 100644 --- a/src/i18n/messages.ts +++ b/src/i18n/messages.ts @@ -249,6 +249,8 @@ const en = { setMarker: (marker: string) => `Set this line's tone to ${marker}`, styleHints: { instruction: "Markers steer this line's tone.", + controlledVocabulary: + "This engine only accepts a fixed style vocabulary; emotion markers are approximations.", intensity: "Chatterbox applies markers as intensity only — more vs. less expressive, not a specific emotion.", suffixTag: @@ -468,6 +470,8 @@ const ru: typeof en = { setMarker: (marker) => `Задать интонацию ${marker}`, styleHints: { instruction: "Маркеры управляют интонацией этой реплики.", + controlledVocabulary: + "Этот движок принимает только фиксированный словарь стилей; эмоции передаются приблизительно.", intensity: "Chatterbox применяет маркеры только как уровень выразительности, а не как конкретную эмоцию.", suffixTag: diff --git a/src/ipc/commands.ts b/src/ipc/commands.ts index f1d4742..5ee11d7 100644 --- a/src/ipc/commands.ts +++ b/src/ipc/commands.ts @@ -24,6 +24,12 @@ export type TtsEngineId = export interface TtsEngineInfo { id: TtsEngineId; displayName: string; + modelName: string; + modelId: string; + modelSize: string; + languages: string[]; + voiceProfileModes: Array<"reference-clone" | "preset-voice" | "designed-voice">; + requiresReferenceAudio: boolean; requiresReferenceTranscript: boolean; /** When true the engine needs a caller-chosen language (e.g. Chatterbox's * `[lang]` token); the UI surfaces a language picker. */ @@ -31,11 +37,24 @@ export interface TtsEngineInfo { /** How inline emotion markers are applied, so the editor can set honest * expectations: * - `instruction`: marker → a natural-language style instruction (real tone). + * - `controlled-vocabulary`: marker → fixed model vocabulary (limited tone). * - `intensity`: marker → an expressiveness level only (not a specific emotion). * - `suffix-tag`: marker → an engine-specific suffix tag such as ``. * - `bracket-tag`: marker → an engine-specific suffix tag such as `[excited]`. * - `none`: markers are ignored. */ - styleMode: "instruction" | "intensity" | "suffix-tag" | "bracket-tag" | "none"; + styleMode: + | "instruction" + | "controlled-vocabulary" + | "intensity" + | "suffix-tag" + | "bracket-tag" + | "none"; + supportsInstruct: boolean; + supportedMarkers: string[]; + needsTrim: boolean; + sampleRate: number; + usePolicy: "commercial-safe" | "research-only" | "needs-review" | string; + readiness: "production" | "legacy-fallback" | "benchmark" | "experimental" | string; } export function availableTtsEngines(): Promise { diff --git a/src/state/projectStore.test.ts b/src/state/projectStore.test.ts index 784e55b..0365a13 100644 --- a/src/state/projectStore.test.ts +++ b/src/state/projectStore.test.ts @@ -1,6 +1,33 @@ import { beforeEach, describe, expect, it } from "vitest"; import { newClip, useProjectStore } from "./projectStore"; import { emptyProject, type SpeakerTrack, type VideoTrack } from "../types/project"; +import type { TtsEngineInfo } from "../ipc/commands"; + +function engineInfo( + id: TtsEngineInfo["id"], + patch: Partial = {}, +): TtsEngineInfo { + return { + id, + displayName: id, + modelName: id, + modelId: `test/${id}`, + modelSize: "test", + languages: ["en"], + voiceProfileModes: ["reference-clone"], + requiresReferenceAudio: true, + requiresReferenceTranscript: false, + requiresLanguage: false, + styleMode: "instruction", + supportsInstruct: true, + supportedMarkers: [], + needsTrim: true, + sampleRate: 24_000, + usePolicy: "commercial-safe", + readiness: "production", + ...patch, + }; +} function speakerTrack(name = "Speaker 1"): SpeakerTrack { return { @@ -32,6 +59,34 @@ describe("projectStore model defaults", () => { it("starts on CosyVoice so macOS loads it by default", () => { expect(useProjectStore.getState().model.engine).toBe("cosyvoice"); }); + + it("normalizes the current language when engine descriptors arrive", () => { + useProjectStore.setState((s) => ({ + model: { ...s.model, engine: "chatterbox", language: "xx" }, + })); + useProjectStore + .getState() + .setAvailableTtsEngines([ + engineInfo("chatterbox", { languages: ["hi", "en"], requiresLanguage: true }), + ]); + expect(useProjectStore.getState().model.language).toBe("hi"); + }); + + it("uses the selected engine's first language when switching engines", () => { + useProjectStore.setState((s) => ({ + model: { + ...s.model, + engine: "cosyvoice", + language: "ru", + engines: [ + engineInfo("cosyvoice", { languages: ["en", "zh"] }), + engineInfo("chatterbox", { languages: ["hi", "en"], requiresLanguage: true }), + ], + }, + })); + useProjectStore.getState().setTtsEngine("chatterbox"); + expect(useProjectStore.getState().model.language).toBe("hi"); + }); }); describe("projectStore.addTrack / removeTrack", () => { diff --git a/src/state/projectStore.ts b/src/state/projectStore.ts index 955625c..c733902 100644 --- a/src/state/projectStore.ts +++ b/src/state/projectStore.ts @@ -205,18 +205,34 @@ export const useProjectStore = create((set) => ({ : s, ), setTtsEngine: (engine) => - set((s) => ({ - model: { - ...s.model, - engine, - language: engine === "indic-mio" ? "hi" : s.model.language, - error: undefined, - }, - })), + set((s) => { + const nextEngine = s.model.engines.find((candidate) => candidate.id === engine); + const languages = nextEngine?.languages ?? []; + const language = languages.length && !languages.includes(s.model.language) + ? languages[0] + : engine === "indic-mio" + ? "hi" + : s.model.language; + return { + model: { + ...s.model, + engine, + language, + error: undefined, + }, + }; + }), setTtsLanguage: (language) => set((s) => ({ model: { ...s.model, language, error: undefined } })), setAvailableTtsEngines: (engines) => - set((s) => ({ model: { ...s.model, engines } })), + set((s) => { + const active = engines.find((candidate) => candidate.id === s.model.engine); + const languages = active?.languages ?? []; + const language = languages.length && !languages.includes(s.model.language) + ? languages[0] + : s.model.language; + return { model: { ...s.model, engines, language } }; + }), demoProgress: null, setDemoProgress: (p) => set(() => ({ demoProgress: p })), diff --git a/src/types/project.ts b/src/types/project.ts index 654acbf..9cb4829 100644 --- a/src/types/project.ts +++ b/src/types/project.ts @@ -1,7 +1,5 @@ -// Tag names recognised by the sidecar's emotionInstructs map. Wrap a line -// with one of these (XML-style `…` or leading parenthetical -// `(tag) …`) and the sidecar passes the matching natural-language style -// instruction to VoxCPM2's `instruct` channel. +// Default marker names for instruction-style engines. Engine descriptors can +// provide a narrower marker palette for suffix/bracket/vocabulary models. export const EMOTION_TAGS = [ "soft", "warm", From 2f6768df97255bb7cd1cb7e4a9df882af7d976a4 Mon Sep 17 00:00:00 2001 From: ivan-digital Date: Sat, 4 Jul 2026 10:13:10 +0200 Subject: [PATCH 2/6] Move TTS capability registry into Studio --- src-tauri/src/lib.rs | 558 ++++++++++++++++++++++++------------------- 1 file changed, 306 insertions(+), 252 deletions(-) diff --git a/src-tauri/src/lib.rs b/src-tauri/src/lib.rs index 04babf1..1a38d81 100644 --- a/src-tauri/src/lib.rs +++ b/src-tauri/src/lib.rs @@ -382,100 +382,286 @@ enum TtsEngine { FishAudio, } -impl TtsEngine { - fn sidecar_command(self) -> &'static str { - match self { - Self::VoxCPM2 => "synthesize_voxcpm2", - Self::CosyVoice => "synthesize_cosyvoice", - Self::Qwen3 => "synthesize_icl", - Self::Chatterbox => "synthesize_chatterbox", - Self::OmniVoice => "synthesize_omnivoice", - Self::IndicMio => "synthesize_indic_mio", - Self::FishAudio => "synthesize_fish_audio", - } - } - - fn display_name(self) -> &'static str { - match self { - Self::VoxCPM2 => "VoxCPM2", - Self::CosyVoice => "CosyVoice 3", - Self::Qwen3 => "Qwen3-TTS", - Self::Chatterbox => "Chatterbox", - Self::OmniVoice => "OmniVoice", - Self::IndicMio => "Indic-Mio", - Self::FishAudio => "Fish Audio S2 Pro", - } - } - - fn model_name(self) -> &'static str { - match self { - Self::VoxCPM2 => "voxcpm2-mlx-int8", - Self::CosyVoice => "cosyvoice-3-0.5b-mlx-bf16", - Self::Qwen3 => "qwen3-tts-1.7b-mlx-bf16", - Self::Chatterbox => "chatterbox-multilingual-mlx-fp16", - Self::OmniVoice => "omnivoice-mlx-int8", - Self::IndicMio => "indic-mio-mlx-fp16", - Self::FishAudio => "fish-audio-s2-pro-mlx-fp16", - } - } +#[derive(Clone, Copy, Serialize)] +struct TtsEngineInfo { + id: TtsEngine, + #[serde(rename = "displayName")] + display_name: &'static str, + #[serde(rename = "modelName")] + model_name: &'static str, + #[serde(rename = "modelId")] + model_id: &'static str, + #[serde(rename = "modelSize")] + model_size: &'static str, + languages: &'static [&'static str], + #[serde(rename = "voiceProfileModes")] + voice_profile_modes: &'static [&'static str], + #[serde(rename = "requiresReferenceAudio")] + requires_reference_audio: bool, + #[serde(rename = "requiresReferenceTranscript")] + requires_reference_transcript: bool, + #[serde(rename = "requiresLanguage")] + requires_language: bool, + #[serde(rename = "styleMode")] + style_mode: &'static str, + #[serde(rename = "supportsInstruct")] + supports_instruct: bool, + #[serde(rename = "supportedMarkers")] + supported_markers: &'static [&'static str], + #[serde(rename = "needsTrim")] + needs_trim: bool, + #[serde(rename = "sampleRate")] + sample_rate: u32, + #[serde(rename = "usePolicy")] + use_policy: &'static str, + readiness: &'static str, +} - fn model_id(self) -> &'static str { - match self { - Self::VoxCPM2 => "aufklarer/VoxCPM2-MLX-int8", - Self::CosyVoice => "aufklarer/CosyVoice3-0.5B-MLX-bf16", - Self::Qwen3 => "aufklarer/Qwen3-TTS-12Hz-1.7B-Base-MLX-bf16", - Self::Chatterbox => "aufklarer/Chatterbox-Multilingual-MLX-fp16", - Self::OmniVoice => "aufklarer/OmniVoice-MLX-int8", - Self::IndicMio => "aufklarer/Indic-Mio-MLX-fp16", - Self::FishAudio => "aufklarer/Fish-Audio-S2-Pro-MLX-fp16", - } - } +#[derive(Clone, Copy)] +struct TtsEngineRegistryEntry { + info: TtsEngineInfo, + sidecar_command: &'static str, + macos_only: bool, +} + +const REFERENCE_CLONE_PROFILE: &[&str] = &["reference-clone"]; +const EN_ZH_LANGUAGES: &[&str] = &["en", "zh"]; +const QWEN_TTS_LANGUAGES: &[&str] = &["zh", "en", "ja", "ko", "de", "fr", "ru", "pt", "es", "it"]; +const CHATTERBOX_LANGUAGES: &[&str] = &[ + "ar", "da", "de", "el", "en", "es", "fi", "fr", "he", "hi", "it", "ja", "ko", "ms", "nl", "no", + "pl", "pt", "ru", "sv", "sw", "tr", "zh", +]; +const OMNIVOICE_LANGUAGES: &[&str] = &[ + "en", "hi", "ru", "es", "fr", "de", "it", "pt", "zh", "ja", "ko", +]; +const HI_EN_LANGUAGES: &[&str] = &["hi", "en"]; +const INSTRUCTION_MARKERS: &[&str] = &[ + "soft", + "warm", + "whispering", + "intense", + "excited", + "happy", + "calm", + "serious", + "surprised", + "sad", + "angry", + "dramatic", + "laughs", +]; +const OMNIVOICE_MARKERS: &[&str] = &[ + "whispering", + "excited", + "happy", + "calm", + "serious", + "sad", + "angry", +]; +const INDIC_MIO_MARKERS: &[&str] = &["happy", "sad", "angry", "disgust", "fear", "surprise"]; +const FISH_AUDIO_MARKERS: &[&str] = &[ + "pause", + "emphasis", + "laughing", + "excited", + "angry", + "whisper", + "screaming", + "shouting", + "surprised", + "sad", +]; + +const TTS_ENGINE_REGISTRY: &[TtsEngineRegistryEntry] = &[ + TtsEngineRegistryEntry { + info: TtsEngineInfo { + id: TtsEngine::VoxCPM2, + display_name: "VoxCPM2", + model_name: "voxcpm2-mlx-int8", + model_id: "aufklarer/VoxCPM2-MLX-int8", + model_size: "1.7B", + languages: EN_ZH_LANGUAGES, + voice_profile_modes: REFERENCE_CLONE_PROFILE, + requires_reference_audio: true, + requires_reference_transcript: false, + requires_language: false, + style_mode: "instruction", + supports_instruct: true, + supported_markers: INSTRUCTION_MARKERS, + needs_trim: true, + sample_rate: 48_000, + use_policy: "commercial-safe", + readiness: "production", + }, + sidecar_command: "synthesize_voxcpm2", + macos_only: false, + }, + TtsEngineRegistryEntry { + info: TtsEngineInfo { + id: TtsEngine::CosyVoice, + display_name: "CosyVoice 3", + model_name: "cosyvoice-3-0.5b-mlx-bf16", + model_id: "aufklarer/CosyVoice3-0.5B-MLX-bf16", + model_size: "0.5B", + languages: EN_ZH_LANGUAGES, + voice_profile_modes: REFERENCE_CLONE_PROFILE, + requires_reference_audio: true, + requires_reference_transcript: true, + requires_language: false, + style_mode: "instruction", + supports_instruct: true, + supported_markers: INSTRUCTION_MARKERS, + needs_trim: true, + sample_rate: 24_000, + use_policy: "commercial-safe", + readiness: "production", + }, + sidecar_command: "synthesize_cosyvoice", + macos_only: true, + }, + TtsEngineRegistryEntry { + info: TtsEngineInfo { + id: TtsEngine::Qwen3, + display_name: "Qwen3-TTS", + model_name: "qwen3-tts-1.7b-mlx-bf16", + model_id: "aufklarer/Qwen3-TTS-12Hz-1.7B-Base-MLX-bf16", + model_size: "1.7B", + languages: QWEN_TTS_LANGUAGES, + voice_profile_modes: REFERENCE_CLONE_PROFILE, + requires_reference_audio: true, + requires_reference_transcript: true, + requires_language: false, + style_mode: "none", + supports_instruct: false, + supported_markers: &[], + needs_trim: true, + sample_rate: 24_000, + use_policy: "commercial-safe", + readiness: "legacy-fallback", + }, + sidecar_command: "synthesize_icl", + macos_only: true, + }, + TtsEngineRegistryEntry { + info: TtsEngineInfo { + id: TtsEngine::Chatterbox, + display_name: "Chatterbox", + model_name: "chatterbox-multilingual-mlx-fp16", + model_id: "aufklarer/Chatterbox-Multilingual-MLX-fp16", + model_size: "0.5B", + languages: CHATTERBOX_LANGUAGES, + voice_profile_modes: REFERENCE_CLONE_PROFILE, + requires_reference_audio: true, + requires_reference_transcript: false, + requires_language: true, + style_mode: "intensity", + supports_instruct: false, + supported_markers: INSTRUCTION_MARKERS, + needs_trim: true, + sample_rate: 24_000, + use_policy: "commercial-safe", + readiness: "production", + }, + sidecar_command: "synthesize_chatterbox", + macos_only: true, + }, + TtsEngineRegistryEntry { + info: TtsEngineInfo { + id: TtsEngine::OmniVoice, + display_name: "OmniVoice", + model_name: "omnivoice-mlx-int8", + model_id: "aufklarer/OmniVoice-MLX-int8", + model_size: "0.5B", + languages: OMNIVOICE_LANGUAGES, + voice_profile_modes: REFERENCE_CLONE_PROFILE, + requires_reference_audio: true, + requires_reference_transcript: false, + requires_language: true, + style_mode: "controlled-vocabulary", + supports_instruct: false, + supported_markers: OMNIVOICE_MARKERS, + needs_trim: true, + sample_rate: 24_000, + use_policy: "commercial-safe", + readiness: "production", + }, + sidecar_command: "synthesize_omnivoice", + macos_only: true, + }, + TtsEngineRegistryEntry { + info: TtsEngineInfo { + id: TtsEngine::IndicMio, + display_name: "Indic-Mio", + model_name: "indic-mio-mlx-fp16", + model_id: "aufklarer/Indic-Mio-MLX-fp16", + model_size: "0.6B", + languages: HI_EN_LANGUAGES, + voice_profile_modes: REFERENCE_CLONE_PROFILE, + requires_reference_audio: true, + requires_reference_transcript: false, + requires_language: false, + style_mode: "suffix-tag", + supports_instruct: false, + supported_markers: INDIC_MIO_MARKERS, + needs_trim: true, + sample_rate: 24_000, + use_policy: "commercial-safe", + readiness: "production", + }, + sidecar_command: "synthesize_indic_mio", + macos_only: true, + }, + TtsEngineRegistryEntry { + info: TtsEngineInfo { + id: TtsEngine::FishAudio, + display_name: "Fish Audio S2 Pro", + model_name: "fish-audio-s2-pro-mlx-fp16", + model_id: "aufklarer/Fish-Audio-S2-Pro-MLX-fp16", + model_size: "S2 Pro", + languages: HI_EN_LANGUAGES, + voice_profile_modes: REFERENCE_CLONE_PROFILE, + requires_reference_audio: true, + requires_reference_transcript: true, + requires_language: false, + style_mode: "bracket-tag", + supports_instruct: false, + supported_markers: FISH_AUDIO_MARKERS, + needs_trim: false, + sample_rate: 44_100, + use_policy: "research-only", + readiness: "benchmark", + }, + sidecar_command: "synthesize_fish_audio", + macos_only: true, + }, +]; - fn model_size(self) -> &'static str { - match self { - Self::CosyVoice => "0.5B", - Self::Qwen3 => "1.7B", - Self::Chatterbox => "0.5B", - Self::OmniVoice => "0.5B", - Self::IndicMio => "0.6B", - Self::VoxCPM2 => "1.7B", - Self::FishAudio => "S2 Pro", - } +impl TtsEngine { + fn registry_entry(self) -> &'static TtsEngineRegistryEntry { + TTS_ENGINE_REGISTRY + .iter() + .find(|entry| entry.info.id == self) + .expect("TtsEngine missing from TTS_ENGINE_REGISTRY") } - fn languages(self) -> &'static [&'static str] { - match self { - Self::Qwen3 => &["zh", "en", "ja", "ko", "de", "fr", "ru", "pt", "es", "it"], - Self::Chatterbox => &[ - "ar", "da", "de", "el", "en", "es", "fi", "fr", "he", "hi", "it", "ja", "ko", "ms", - "nl", "no", "pl", "pt", "ru", "sv", "sw", "tr", "zh", - ], - Self::OmniVoice => &[ - "en", "hi", "ru", "es", "fr", "de", "it", "pt", "zh", "ja", "ko", - ], - Self::IndicMio => &["hi", "en"], - Self::FishAudio => &["hi", "en"], - Self::VoxCPM2 | Self::CosyVoice => &["en", "zh"], - } + fn sidecar_command(self) -> &'static str { + self.registry_entry().sidecar_command } - fn voice_profile_modes(self) -> &'static [&'static str] { - &["reference-clone"] + fn display_name(self) -> &'static str { + self.registry_entry().info.display_name } fn requires_reference_transcript(self) -> bool { - matches!(self, Self::CosyVoice | Self::Qwen3 | Self::FishAudio) - } - - fn requires_reference_audio(self) -> bool { - true + self.registry_entry().info.requires_reference_transcript } /// Whether synthesis needs a caller-chosen language. Chatterbox prepends a /// `[lang]` token, so the Studio shows a language picker for it; the other /// engines infer language from the text. fn requires_language(self) -> bool { - matches!(self, Self::Chatterbox | Self::OmniVoice) + self.registry_entry().info.requires_language } /// How the engine applies inline emotion markers — drives the editor hint: @@ -487,105 +673,7 @@ impl TtsEngine { /// - `bracket-tag`: marker is appended as an engine-specific bracket tag. /// - `none`: markers are stripped and ignored. fn style_mode(self) -> &'static str { - match self { - Self::VoxCPM2 | Self::CosyVoice => "instruction", - Self::OmniVoice => "controlled-vocabulary", - Self::Chatterbox => "intensity", - Self::IndicMio => "suffix-tag", - Self::FishAudio => "bracket-tag", - Self::Qwen3 => "none", - } - } - - fn supports_instruct(self) -> bool { - matches!(self, Self::VoxCPM2 | Self::CosyVoice) - } - - fn supported_markers(self) -> &'static [&'static str] { - match self { - Self::VoxCPM2 | Self::CosyVoice => &[ - "soft", - "warm", - "whispering", - "intense", - "excited", - "happy", - "calm", - "serious", - "surprised", - "sad", - "angry", - "dramatic", - "laughs", - ], - Self::OmniVoice => &[ - "whispering", - "excited", - "happy", - "calm", - "serious", - "sad", - "angry", - ], - Self::Chatterbox => &[ - "soft", - "warm", - "whispering", - "intense", - "excited", - "happy", - "calm", - "serious", - "surprised", - "sad", - "angry", - "dramatic", - "laughs", - ], - Self::IndicMio => &["happy", "sad", "angry", "disgust", "fear", "surprise"], - Self::FishAudio => &[ - "pause", - "emphasis", - "laughing", - "excited", - "angry", - "whisper", - "screaming", - "shouting", - "surprised", - "sad", - ], - Self::Qwen3 => &[], - } - } - - fn needs_trim(self) -> bool { - trim_long_form_chunk_edges(self) - } - - fn sample_rate(self) -> u32 { - match self { - Self::VoxCPM2 => 48_000, - Self::FishAudio => 44_100, - Self::CosyVoice | Self::Qwen3 | Self::Chatterbox | Self::OmniVoice | Self::IndicMio => { - 24_000 - } - } - } - - fn use_policy(self) -> &'static str { - match self { - Self::FishAudio => "research-only", - _ => "commercial-safe", - } - } - - fn readiness(self) -> &'static str { - match self { - Self::Qwen3 => "legacy-fallback", - Self::FishAudio => "benchmark", - _ => "production", - } + self.registry_entry().info.style_mode } } @@ -605,15 +693,8 @@ fn normalize_sidecar_language(engine: TtsEngine, language: Option<&str>) -> Opti } fn engine_is_supported(engine: TtsEngine) -> bool { - match engine { - TtsEngine::VoxCPM2 => true, - TtsEngine::CosyVoice => cfg!(target_os = "macos"), - TtsEngine::Qwen3 => cfg!(target_os = "macos"), - TtsEngine::Chatterbox => cfg!(target_os = "macos"), - TtsEngine::OmniVoice => cfg!(target_os = "macos"), - TtsEngine::IndicMio => cfg!(target_os = "macos"), - TtsEngine::FishAudio => cfg!(target_os = "macos"), - } + let entry = engine.registry_entry(); + !entry.macos_only || cfg!(target_os = "macos") } fn ensure_engine_supported(engine: TtsEngine) -> Result<(), String> { @@ -650,75 +731,17 @@ fn humanize_sidecar_error(engine: TtsEngine, error: String) -> String { error } -#[derive(Serialize)] -struct TtsEngineInfo { - id: TtsEngine, - #[serde(rename = "displayName")] - display_name: &'static str, - #[serde(rename = "modelName")] - model_name: &'static str, - #[serde(rename = "modelId")] - model_id: &'static str, - #[serde(rename = "modelSize")] - model_size: &'static str, - languages: &'static [&'static str], - #[serde(rename = "voiceProfileModes")] - voice_profile_modes: &'static [&'static str], - #[serde(rename = "requiresReferenceAudio")] - requires_reference_audio: bool, - #[serde(rename = "requiresReferenceTranscript")] - requires_reference_transcript: bool, - #[serde(rename = "requiresLanguage")] - requires_language: bool, - #[serde(rename = "styleMode")] - style_mode: &'static str, - #[serde(rename = "supportsInstruct")] - supports_instruct: bool, - #[serde(rename = "supportedMarkers")] - supported_markers: &'static [&'static str], - #[serde(rename = "needsTrim")] - needs_trim: bool, - #[serde(rename = "sampleRate")] - sample_rate: u32, - #[serde(rename = "usePolicy")] - use_policy: &'static str, - readiness: &'static str, -} - fn tts_engine_info(engine: TtsEngine) -> TtsEngineInfo { - TtsEngineInfo { - id: engine, - display_name: engine.display_name(), - model_name: engine.model_name(), - model_id: engine.model_id(), - model_size: engine.model_size(), - languages: engine.languages(), - voice_profile_modes: engine.voice_profile_modes(), - requires_reference_audio: engine.requires_reference_audio(), - requires_reference_transcript: engine.requires_reference_transcript(), - requires_language: engine.requires_language(), - style_mode: engine.style_mode(), - supports_instruct: engine.supports_instruct(), - supported_markers: engine.supported_markers(), - needs_trim: engine.needs_trim(), - sample_rate: engine.sample_rate(), - use_policy: engine.use_policy(), - readiness: engine.readiness(), - } + engine.registry_entry().info } #[tauri::command] async fn available_tts_engines() -> Vec { - let mut engines = vec![tts_engine_info(TtsEngine::VoxCPM2)]; - if cfg!(target_os = "macos") { - engines.push(tts_engine_info(TtsEngine::CosyVoice)); - engines.push(tts_engine_info(TtsEngine::Qwen3)); - engines.push(tts_engine_info(TtsEngine::Chatterbox)); - engines.push(tts_engine_info(TtsEngine::OmniVoice)); - engines.push(tts_engine_info(TtsEngine::IndicMio)); - engines.push(tts_engine_info(TtsEngine::FishAudio)); - } - engines + TTS_ENGINE_REGISTRY + .iter() + .filter(|entry| engine_is_supported(entry.info.id)) + .map(|entry| entry.info) + .collect() } #[tauri::command] @@ -1448,7 +1471,7 @@ const MAX_CHUNK_WORDS: usize = 14; const CHUNK_GAP_SEC: f64 = 0.28; fn trim_long_form_chunk_edges(engine: TtsEngine) -> bool { - !matches!(engine, TtsEngine::FishAudio) + engine.registry_entry().info.needs_trim } /// Trim leading/trailing low-energy tails from a rendered chunk. The model @@ -3129,6 +3152,37 @@ mod tests { assert!(!fish.needs_trim); } + #[test] + fn studio_registry_keeps_qwen_on_bf16() { + let ids: Vec = TTS_ENGINE_REGISTRY + .iter() + .map(|entry| entry.info.id) + .collect(); + assert_eq!( + ids, + vec![ + TtsEngine::VoxCPM2, + TtsEngine::CosyVoice, + TtsEngine::Qwen3, + TtsEngine::Chatterbox, + TtsEngine::OmniVoice, + TtsEngine::IndicMio, + TtsEngine::FishAudio, + ] + ); + + let qwen = TtsEngine::Qwen3.registry_entry(); + assert_eq!(qwen.info.model_name, "qwen3-tts-1.7b-mlx-bf16"); + assert_eq!( + qwen.info.model_id, + "aufklarer/Qwen3-TTS-12Hz-1.7B-Base-MLX-bf16" + ); + assert!(!qwen.info.model_name.contains("8bit")); + assert!(!qwen.info.model_id.contains("8bit")); + assert!(!qwen.info.model_name.contains("0.6b")); + assert_eq!(qwen.info.style_mode, "none"); + } + #[test] fn sidecar_language_normalization_preserves_chatterbox_hi() { assert_eq!( From b28f2c6455ce013d2b9bfe1216a35aac55eabbea Mon Sep 17 00:00:00 2001 From: ivan-digital Date: Sun, 5 Jul 2026 12:29:06 +0200 Subject: [PATCH 3/6] Finish registry rollout: dictation, synthesis hardening, demo voices MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Ship the remaining pieces on top of the capability registry: Dictation: Parakeet ASR through the sidecar (transcribe_parakeet), a save-and-transcribe IPC path with its own cache dir, an ASR model registry, and a DictationPanel front end. Model plumbing: pass the registry-selected modelId through init_model and the synthesize commands so holders reload when the artifact changes; default VoxCPM2 to the bf16 bundle; registry-driven per-engine seed ladders, token budgets, and language normalization. Synthesis output conditioning: every engine's WAV now gets a silent lead-in, edge fades, and a post-roll (conditionAudioEdges). Qwen3 ICL and OmniVoice additionally open some renders (reference-dependent) with a short low-level codec artifact before the first word — quiet hiss on the Marek reference, a low hum on Anna — followed by a silence gap. trimLeadingJunk removes it via energy-island analysis: leading islands that are short, early, gap-separated, and either ≥20 dB below the loudest island or 8-20 dB below with a pure low-frequency ZCR signature. Clean renders pass through bit-exact. A fixed pre-trim could not work here: the residue runs past 150 ms on affected renders while unaffected ones start voiced within 25 ms. Indic-Mio markers: map the Studio's inline emotion markers onto the model's closed suffix-tag vocabulary. The model reads unknown parentheticals aloud, so unmapped markers are dropped rather than passed through. Demo: lazy clip seeding with stable cache ids; exact bundled reference transcripts (a stale Anna transcript leaked prompt words into takes); Qwen goes single-shot at a fixed seed; the Hindi demo gains a second, female FLEURS speaker (the existing reference is the male recording of its sentence) with lines alternating across both voices. Tests: sidecar e2e for onset cleanliness on both affected engines and marker handling on Indic-Mio (ignored, model-backed), fast protocol tests for engine mismatch and missing fields, and frontend unit tests for the new synth, clip-audio, media-src, and language helpers. --- core-sidecar/CMakeLists.txt | 1 + core-sidecar/src/main.cpp | 175 ++++ model-registry.json | 460 +++++++++ scripts/tts_roundtrip_matrix.py | 804 +++++++++++++++ src-tauri/Cargo.lock | 1 + src-tauri/Cargo.toml | 1 + src-tauri/resources/voices/hindi_fleurs.wav | Bin 0 -> 122924 bytes .../resources/voices/hindi_fleurs_female.wav | Bin 0 -> 282284 bytes src-tauri/src/lib.rs | 942 ++++++++++++------ src-tauri/tests/sidecar.rs | 272 ++++- src/components/DictationPanel.tsx | 408 ++++++++ src/components/Inspector.tsx | 14 +- src/components/LeftRail.tsx | 19 +- src/components/ProjectsMenu.tsx | 44 +- src/components/ScriptEditor.test.tsx | 2 + src/components/TopBar.tsx | 70 +- src/hooks/useAudioScheduler.ts | 8 +- src/hooks/useSynthesizeAll.test.tsx | 101 ++ src/hooks/useSynthesizeAll.ts | 10 +- src/i18n/messages.ts | 65 ++ src/ipc/commands.ts | 60 +- src/lib/clipAudio.test.ts | 57 ++ src/lib/clipAudio.ts | 6 + src/lib/languageLabels.test.ts | 48 + src/lib/languageLabels.ts | 36 + src/lib/mediaSrc.test.ts | 18 + src/lib/mediaSrc.ts | 8 + src/state/demoProject.ts | 157 ++- src/state/projectStore.test.ts | 41 + src/state/projectStore.ts | 32 +- swift-sidecar/Package.swift | 2 + .../Sources/soniqo-tts-sidecar/main.swift | 383 +++++-- 32 files changed, 3788 insertions(+), 457 deletions(-) create mode 100644 model-registry.json create mode 100644 scripts/tts_roundtrip_matrix.py create mode 100644 src-tauri/resources/voices/hindi_fleurs.wav create mode 100644 src-tauri/resources/voices/hindi_fleurs_female.wav create mode 100644 src/components/DictationPanel.tsx create mode 100644 src/hooks/useSynthesizeAll.test.tsx create mode 100644 src/lib/clipAudio.test.ts create mode 100644 src/lib/languageLabels.test.ts create mode 100644 src/lib/languageLabels.ts create mode 100644 src/lib/mediaSrc.test.ts create mode 100644 src/lib/mediaSrc.ts diff --git a/core-sidecar/CMakeLists.txt b/core-sidecar/CMakeLists.txt index 25c2577..e87d62a 100644 --- a/core-sidecar/CMakeLists.txt +++ b/core-sidecar/CMakeLists.txt @@ -68,6 +68,7 @@ find_package(CURL REQUIRED) add_executable(speech-core-tts-sidecar src/main.cpp src/audio_decode.cpp src/sidecar_text.cpp src/sidecar_sysinfo.cpp) target_include_directories(speech-core-tts-sidecar PRIVATE "${SPEECH_CORE_DIR}/include" + "${SPEECH_CORE_DIR}/src/models/litert" # Vendored LiteRT C API headers — needed since the transcribe command uses # speech-core's C++ LiteRT wrappers directly (litert_engine.h). "${SPEECH_CORE_DIR}/third_party/litert" diff --git a/core-sidecar/src/main.cpp b/core-sidecar/src/main.cpp index d527a9c..402ea2c 100644 --- a/core-sidecar/src/main.cpp +++ b/core-sidecar/src/main.cpp @@ -20,16 +20,20 @@ // transcribe — ASR a rendered take (Omnilingual CTC-300M) so the // host can grade it against the target text and // retry bad takes. Model dir comes per-request. +// transcribe_parakeet — user dictation / transcription with Parakeet TDT v3. #include #include #include +#include #include +#include "hf_download.h" #include "audio_decode.h" #include "sidecar_text.h" #include "sidecar_sysinfo.h" +#include #include #include #include @@ -40,6 +44,7 @@ #include #include #include +#include #include #include #include @@ -138,6 +143,38 @@ static fs::path clips_cache_dir() { return dir; } +static std::string model_cache_root() { + if (const char* c = std::getenv("SONIQO_MODEL_CACHE_DIR"); c && *c) return c; + if (const char* c = std::getenv("SPEECH_CORE_CACHE_DIR"); c && *c) return c; +#if defined(_WIN32) + if (const char* la = std::getenv("LOCALAPPDATA"); la && *la) + return std::string(la) + "/speech-core"; +#elif defined(__APPLE__) + if (const char* h = std::getenv("HOME"); h && *h) + return std::string(h) + "/Library/Caches/speech-core"; +#else + if (const char* x = std::getenv("XDG_CACHE_HOME"); x && *x) + return std::string(x) + "/speech-core"; + if (const char* h = std::getenv("HOME"); h && *h) + return std::string(h) + "/.cache/speech-core"; +#endif + return "./speech-core-cache"; +} + +static std::string sanitize_repo_id(const std::string& id) { + std::string s; + for (char c : id) { + if (c == '/' || c == '\\') s += "__"; + else s += c; + } + return s; +} + +static std::string format_mb(uint64_t bytes) { + const uint64_t mb = 1024ull * 1024ull; + return std::to_string((bytes + mb - 1) / mb) + " MB"; +} + // --------------------------------------------------------------------------- // VoxCPM2 model state (one warm handle across calls) // --------------------------------------------------------------------------- @@ -343,6 +380,142 @@ static void handle_transcribe(const json::Dict& req, const std::string& id) { "\"text\":\"" + json_escape(res.text) + "\"}}"); } +// transcribe_parakeet — user-facing dictation/transcription. Uses the same +// logical Parakeet TDT v3 family as the macOS sidecar, backed by the LiteRT +// INT8 bundle on Windows/Linux. The bundle is downloaded on first use unless +// SONIQO_PARAKEET_BUNDLE_DIR points at a pre-provisioned directory. +static std::unique_ptr g_parakeet; +static std::string g_parakeet_dir; +static std::string g_parakeet_model_id; + +static void on_parakeet_download_progress(const std::string& file, int idx, int count, + uint64_t downloaded, uint64_t total) { + static std::string last_file; + static int last_pct = -1; + if (last_file != file) { + last_file = file; + last_pct = -1; + } + const double file_fraction = total ? static_cast(downloaded) / total : 0.0; + const double overall = count > 0 + ? ((static_cast(idx) + file_fraction) / static_cast(count)) * 100.0 + : file_fraction * 100.0; + const int pct = static_cast(overall + 0.5); + if (pct != last_pct && (pct % 5 == 0 || pct == 100)) { + last_pct = pct; + std::string detail = "Downloading Parakeet"; + if (total) detail += " " + format_mb(downloaded) + " / " + format_mb(total); + log_err("[sidecar] parakeet " + std::to_string(pct) + "% " + detail); + } +} + +static bool parakeet_bundle_exists(const std::string& dir) { + return fs::exists(fs::path(dir) / "parakeet-encoder.tflite") && + fs::exists(fs::path(dir) / "parakeet-decoder-joint.tflite") && + fs::exists(fs::path(dir) / "vocab.json"); +} + +static std::string ensure_parakeet_bundle(std::string& model_id_out) { + std::string dir = env_or("SONIQO_PARAKEET_BUNDLE_DIR", ""); + if (!dir.empty()) { + if (!parakeet_bundle_exists(dir)) { + throw std::runtime_error( + "Parakeet bundle not found at " + dir + + " (expected parakeet-encoder.tflite, parakeet-decoder-joint.tflite, vocab.json)"); + } + model_id_out = env_or("SONIQO_PARAKEET_MODEL_ID", + "soniqo/Parakeet-TDT-0.6B-v3-LiteRT-INT8"); + return dir; + } + + if (!speech_core::hf::download_supported()) { + throw std::runtime_error( + "SONIQO_PARAKEET_BUNDLE_DIR is unset and this speech-core build has no " + "model-download support (rebuild with -DSPEECH_CORE_WITH_HF_DOWNLOAD=ON)"); + } + + const std::string model_id = env_or("SONIQO_PARAKEET_MODEL_ID", + "soniqo/Parakeet-TDT-0.6B-v3-LiteRT-INT8"); + const std::string dir_out = model_cache_root() + "/" + sanitize_repo_id(model_id); + if (parakeet_bundle_exists(dir_out)) { + model_id_out = model_id; + return dir_out; + } + const std::vector files = { + "parakeet-encoder.tflite", + "parakeet-decoder-joint.tflite", + "vocab.json", + "config.json", + }; + log_err("[sidecar] ensuring Parakeet ASR bundle " + model_id + " …"); + speech_core::hf::download_bundle( + model_id, "main", files, dir_out, on_parakeet_download_progress); + if (!parakeet_bundle_exists(dir_out)) { + throw std::runtime_error("Parakeet bundle incomplete after download: " + dir_out); + } + model_id_out = model_id; + return dir_out; +} + +static std::string ensure_parakeet_model() { + try { + std::string model_id; + const std::string dir = ensure_parakeet_bundle(model_id); + if (g_parakeet && g_parakeet_dir == dir) return ""; + log_err("[sidecar] loading Parakeet LiteRT bundle from " + dir); + g_parakeet = std::make_unique( + dir + "/parakeet-encoder.tflite", + dir + "/parakeet-decoder-joint.tflite", + dir + "/vocab.json", + /*hw_accel=*/false); + g_parakeet_dir = dir; + g_parakeet_model_id = model_id; + log_err("[sidecar] parakeet ready"); + return ""; + } catch (const std::exception& e) { + g_parakeet.reset(); + return std::string("Parakeet ASR load failed: ") + e.what(); + } +} + +static void handle_transcribe_parakeet(const json::Dict& req, const std::string& id) { + const std::string audio_path = get(req, "audioPath"); + if (audio_path.empty()) { + emit_error(id, "transcribe_parakeet requires audioPath"); + return; + } + + const auto started = std::chrono::steady_clock::now(); + std::vector audio; + int rate = 0; + if (!load_audio_mono(audio_path, audio, rate) || audio.empty()) { + emit_error(id, "could not decode audio: " + audio_path); + return; + } + std::vector a16 = (rate == 16000) + ? std::move(audio) + : speech_core::Resampler::resample(audio.data(), audio.size(), rate, 16000); + + if (std::string err = ensure_parakeet_model(); !err.empty()) { + emit_error(id, err); + return; + } + auto res = g_parakeet->transcribe(a16.data(), a16.size(), 16000); + const double duration = static_cast(a16.size()) / 16000.0; + const double elapsed = std::chrono::duration( + std::chrono::steady_clock::now() - started).count(); + char numeric[160]; + std::snprintf(numeric, sizeof(numeric), + "\"sampleRate\":16000,\"durationSec\":%.6f,\"elapsedSec\":%.6f", + duration, elapsed); + emit_line("{\"id\":\"" + json_escape(id) + "\",\"ok\":true,\"result\":{" + + "\"text\":\"" + json_escape(res.text) + "\"," + + "\"language\":\"" + json_escape(res.language) + "\"," + + "\"modelName\":\"parakeet-tdt-v3-0.6b-int8\"," + + "\"modelId\":\"" + json_escape(g_parakeet_model_id) + "\"," + + numeric + "}}"); +} + static void handle_synthesize(const json::Dict& req, const std::string& id) { const std::string ref_path = get(req, "referenceAudioPath"); const std::string text = get(req, "text"); @@ -485,6 +658,8 @@ int main() { handle_probe(req, id); } else if (command == "transcribe") { handle_transcribe(req, id); + } else if (command == "transcribe_parakeet") { + handle_transcribe_parakeet(req, id); } else { emit_error(id, "unknown command: " + command); } diff --git a/model-registry.json b/model-registry.json new file mode 100644 index 0000000..9c19570 --- /dev/null +++ b/model-registry.json @@ -0,0 +1,460 @@ +{ + "version": 1, + "ttsEngines": [ + { + "id": "voxcpm2", + "displayName": "VoxCPM2", + "modelName": "voxcpm2-mlx-bf16", + "modelId": "aufklarer/VoxCPM2-MLX-bf16", + "modelSize": "1.7B", + "runtime": "MLX", + "precision": "bf16", + "languages": [ + "ar", + "my", + "zh", + "da", + "nl", + "en", + "fi", + "fr", + "de", + "el", + "he", + "hi", + "id", + "it", + "ja", + "km", + "ko", + "lo", + "ms", + "no", + "pl", + "pt", + "ru", + "es", + "sw", + "sv", + "tl", + "th", + "tr", + "vi" + ], + "voiceProfileModes": ["reference-clone"], + "requiresReferenceAudio": true, + "requiresReferenceTranscript": false, + "requiresLanguage": false, + "styleMode": "instruction", + "supportsInstruct": true, + "supportedMarkers": [ + "soft", + "warm", + "whispering", + "intense", + "excited", + "happy", + "calm", + "serious", + "surprised", + "sad", + "angry", + "dramatic", + "laughs" + ], + "needsTrim": true, + "sampleRate": 48000, + "usePolicy": "commercial-safe", + "readiness": "production", + "sidecarCommand": "synthesize_voxcpm2", + "macosOnly": false, + "platformOverrides": { + "linux": { + "modelName": "voxcpm2-litert-fp16", + "modelId": "soniqo/VoxCPM2-LiteRT", + "runtime": "LiteRT", + "precision": "fp16" + }, + "windows": { + "modelName": "voxcpm2-litert-fp16", + "modelId": "soniqo/VoxCPM2-LiteRT", + "runtime": "LiteRT", + "precision": "fp16" + } + } + }, + { + "id": "cosyvoice", + "displayName": "CosyVoice 3", + "modelName": "cosyvoice-3-0.5b-mlx-bf16", + "modelId": "aufklarer/CosyVoice3-0.5B-MLX-bf16", + "modelSize": "0.5B", + "runtime": "MLX", + "precision": "bf16", + "languages": ["en", "zh", "ja", "ko", "de", "es", "fr", "it", "ru"], + "voiceProfileModes": ["reference-clone"], + "requiresReferenceAudio": true, + "requiresReferenceTranscript": true, + "requiresLanguage": true, + "styleMode": "instruction", + "supportsInstruct": true, + "supportedMarkers": [ + "soft", + "warm", + "whispering", + "intense", + "excited", + "happy", + "calm", + "serious", + "surprised", + "sad", + "angry", + "dramatic", + "laughs" + ], + "needsTrim": true, + "sampleRate": 24000, + "usePolicy": "commercial-safe", + "readiness": "production", + "sidecarCommand": "synthesize_cosyvoice", + "macosOnly": true + }, + { + "id": "qwen3", + "displayName": "Qwen3-TTS", + "modelName": "qwen3-tts-1.7b-mlx-bf16", + "modelId": "aufklarer/Qwen3-TTS-12Hz-1.7B-Base-MLX-bf16", + "modelSize": "1.7B", + "runtime": "MLX", + "precision": "bf16", + "languages": ["zh", "en", "ja", "ko", "de", "fr", "ru", "pt", "es", "it"], + "voiceProfileModes": ["reference-clone"], + "requiresReferenceAudio": true, + "requiresReferenceTranscript": true, + "requiresLanguage": true, + "styleMode": "none", + "supportsInstruct": false, + "supportedMarkers": [], + "needsTrim": true, + "sampleRate": 24000, + "usePolicy": "commercial-safe", + "readiness": "legacy-fallback", + "sidecarCommand": "synthesize_icl", + "macosOnly": true + }, + { + "id": "chatterbox", + "displayName": "Chatterbox", + "modelName": "chatterbox-multilingual-mlx-fp16", + "modelId": "aufklarer/Chatterbox-Multilingual-MLX-fp16", + "modelSize": "0.5B", + "runtime": "MLX", + "precision": "fp16", + "languages": [ + "ar", + "da", + "de", + "el", + "en", + "es", + "fi", + "fr", + "hi", + "it", + "ja", + "ko", + "ms", + "nl", + "no", + "pl", + "pt", + "ru", + "sv", + "sw", + "tr", + "zh" + ], + "benchmarkLanguages": [ + "ar", + "da", + "de", + "el", + "en", + "es", + "fi", + "fr", + "hi", + "it", + "ja", + "ko", + "ms", + "nl", + "no", + "pl", + "pt", + "ru", + "sv", + "sw", + "tr", + "zh" + ], + "voiceProfileModes": ["reference-clone"], + "requiresReferenceAudio": true, + "requiresReferenceTranscript": false, + "requiresLanguage": true, + "styleMode": "intensity", + "supportsInstruct": false, + "supportedMarkers": [ + "soft", + "warm", + "whispering", + "intense", + "excited", + "happy", + "calm", + "serious", + "surprised", + "sad", + "angry", + "dramatic", + "laughs" + ], + "needsTrim": true, + "sampleRate": 24000, + "usePolicy": "commercial-safe", + "readiness": "production", + "sidecarCommand": "synthesize_chatterbox", + "macosOnly": true + }, + { + "id": "omnivoice", + "displayName": "OmniVoice", + "modelName": "omnivoice-mlx-fp16", + "modelId": "aufklarer/OmniVoice-MLX-fp16", + "modelSize": "0.5B", + "runtime": "MLX", + "precision": "fp16", + "languages": ["en", "hi", "ru", "es", "fr", "de", "it", "pt", "zh", "ja", "ko"], + "voiceProfileModes": ["reference-clone"], + "requiresReferenceAudio": true, + "requiresReferenceTranscript": false, + "requiresLanguage": true, + "styleMode": "controlled-vocabulary", + "supportsInstruct": false, + "supportedMarkers": [ + "whispering", + "excited", + "happy", + "calm", + "serious", + "sad", + "angry" + ], + "needsTrim": true, + "sampleRate": 24000, + "usePolicy": "commercial-safe", + "readiness": "production", + "sidecarCommand": "synthesize_omnivoice", + "macosOnly": true + }, + { + "id": "indic-mio", + "displayName": "Indic-Mio", + "modelName": "indic-mio-mlx-fp16", + "modelId": "aufklarer/Indic-Mio-MLX-fp16", + "modelSize": "0.6B", + "runtime": "MLX", + "precision": "fp16", + "languages": ["hi", "en"], + "voiceProfileModes": ["reference-clone"], + "requiresReferenceAudio": true, + "requiresReferenceTranscript": false, + "requiresLanguage": false, + "styleMode": "suffix-tag", + "supportsInstruct": false, + "supportedMarkers": ["happy", "sad", "angry", "disgust", "fear", "surprise"], + "needsTrim": true, + "sampleRate": 24000, + "usePolicy": "commercial-safe", + "readiness": "production", + "sidecarCommand": "synthesize_indic_mio", + "macosOnly": true + }, + { + "id": "fish-audio", + "displayName": "Fish Audio S2 Pro", + "modelName": "fish-audio-s2-pro-mlx-fp16", + "modelId": "aufklarer/Fish-Audio-S2-Pro-MLX-fp16", + "modelSize": "S2 Pro", + "runtime": "MLX", + "precision": "fp16", + "languages": [ + "ja", + "en", + "zh", + "ko", + "es", + "pt", + "ar", + "ru", + "fr", + "de", + "sv", + "it", + "tr", + "no", + "nl", + "cy", + "eu", + "ca", + "da", + "gl", + "ta", + "hu", + "fi", + "pl", + "et", + "hi", + "la", + "ur", + "th", + "vi", + "jw", + "bn", + "yo", + "xsl", + "cs", + "sw", + "nn", + "he", + "ms", + "uk", + "id", + "kk", + "bg", + "lv", + "my", + "tl", + "sk", + "ne", + "fa", + "af", + "el", + "bo", + "hr", + "ro", + "sn", + "mi", + "yi", + "am", + "be", + "km", + "is", + "az", + "sd", + "br", + "sq", + "ps", + "mn", + "ht", + "ml", + "sr", + "sa", + "te", + "ka", + "bs", + "pa", + "lt", + "kn", + "si", + "hy", + "mr", + "as", + "gu", + "fo" + ], + "benchmarkLanguages": [ + "ar", + "my", + "zh", + "da", + "nl", + "en", + "fi", + "fr", + "de", + "el", + "he", + "hi", + "id", + "it", + "ja", + "km", + "ko", + "ms", + "no", + "pl", + "pt", + "ru", + "es", + "sw", + "sv", + "tl", + "th", + "tr", + "vi" + ], + "voiceProfileModes": ["reference-clone"], + "requiresReferenceAudio": true, + "requiresReferenceTranscript": true, + "requiresLanguage": false, + "styleMode": "bracket-tag", + "supportsInstruct": false, + "supportedMarkers": [ + "pause", + "emphasis", + "laughing", + "excited", + "angry", + "whisper", + "screaming", + "shouting", + "surprised", + "sad" + ], + "needsTrim": false, + "sampleRate": 44100, + "usePolicy": "research-only", + "readiness": "benchmark", + "sidecarCommand": "synthesize_fish_audio", + "macosOnly": true + } + ], + "asrModels": [ + { + "id": "parakeet-tdt-v3", + "displayName": "Parakeet TDT v3", + "modelName": "parakeet-tdt-v3-0.6b-int8", + "modelId": "aufklarer/Parakeet-TDT-v3-CoreML-INT8-30s", + "modelSize": "0.6B", + "languages": ["en"], + "runtime": "coreml", + "sampleRate": 16000, + "maxSegmentSec": 30, + "streaming": true, + "readiness": "production", + "sidecarCommand": "transcribe_parakeet", + "platformOverrides": { + "linux": { + "modelId": "soniqo/Parakeet-TDT-0.6B-v3-LiteRT-INT8", + "runtime": "litert" + }, + "windows": { + "modelId": "soniqo/Parakeet-TDT-0.6B-v3-LiteRT-INT8", + "runtime": "litert" + } + } + } + ] +} diff --git a/scripts/tts_roundtrip_matrix.py b/scripts/tts_roundtrip_matrix.py new file mode 100644 index 0000000..76197c5 --- /dev/null +++ b/scripts/tts_roundtrip_matrix.py @@ -0,0 +1,804 @@ +#!/usr/bin/env python3 +"""Run a multilingual TTS -> ASR intelligibility matrix against the Swift sidecar. + +The matrix is intentionally a smoke benchmark: one short sentence per +model/language pair, synthesized through the sidecar protocol, transcribed by +the local `speech` CLI, then scored with token precision/recall and WER. +""" + +from __future__ import annotations + +import argparse +import csv +import datetime as dt +import json +import os +import queue +import re +import shutil +import subprocess +import sys +import threading +import time +import unicodedata +from collections import Counter, defaultdict +from dataclasses import dataclass, field +from pathlib import Path +from typing import Any + + +ROOT = Path(__file__).resolve().parents[1] +SIDECAR = ROOT / "swift-sidecar/.build/debug/soniqo-tts-sidecar" +REGISTRY_PATH = ROOT / "model-registry.json" +REF_TEXT = ( + "Hello. This is a clean reference voice spoken slowly and clearly for " + "speech synthesis testing." +) + +TEXTS: dict[str, str] = { + "ar": "اليوم نختبر ما إذا كان الكلام واضحا وسهل الفهم.", + "da": "I dag tester vi, om talen er klar og let at forstå.", + "de": "Heute testen wir, ob die Sprache klar und leicht zu verstehen ist.", + "el": "Σήμερα ελέγχουμε αν η ομιλία είναι καθαρή και εύκολη στην κατανόηση.", + "en": "Today we test whether the speech is clear and easy to understand.", + "es": "Hoy probamos si el habla es clara y fácil de entender.", + "fi": "Tänään testaamme, onko puhe selkeää ja helppoa ymmärtää.", + "fr": "Aujourd'hui, nous testons si la parole est claire et facile à comprendre.", + "he": "היום אנחנו בודקים אם הדיבור ברור וקל להבנה.", + "hi": "आज हम जाँचते हैं कि आवाज़ साफ़ और समझने में आसान है या नहीं।", + "id": "Hari ini kami menguji apakah ucapan jelas dan mudah dipahami.", + "it": "Oggi testiamo se il parlato è chiaro e facile da capire.", + "ja": "今日は音声が明瞭で理解しやすいかをテストします。", + "km": "ថ្ងៃនេះយើងសាកល្បងថាសំឡេងច្បាស់ និងងាយស្រួលយល់ឬអត់។", + "ko": "오늘 우리는 음성이 명확하고 이해하기 쉬운지 테스트합니다.", + "lo": "ມື້ນີ້ພວກເຮົາທົດສອບວ່າສຽງຊັດເຈນ ແລະ ເຂົ້າໃຈງ່າຍຫຼືບໍ່.", + "ms": "Hari ini kami menguji sama ada pertuturan jelas dan mudah difahami.", + "my": "ဒီနေ့ အသံက ရှင်းလင်းပြီး နားလည်ရလွယ်မလွယ် စမ်းသပ်ပါမယ်။", + "nl": "Vandaag testen we of de spraak duidelijk en gemakkelijk te begrijpen is.", + "no": "I dag tester vi om talen er klar og lett å forstå.", + "pl": "Dzisiaj sprawdzamy, czy mowa jest wyraźna i łatwa do zrozumienia.", + "pt": "Hoje testamos se a fala é clara e fácil de entender.", + "ru": "Сегодня мы проверяем, является ли речь четкой и легкой для понимания.", + "sv": "I dag testar vi om talet är tydligt och lätt att förstå.", + "sw": "Leo tunajaribu kama hotuba iko wazi na ni rahisi kuelewa.", + "th": "วันนี้เราทดสอบว่าเสียงพูดชัดเจนและเข้าใจง่ายหรือไม่", + "tl": "Ngayon sinusubukan natin kung malinaw at madaling maunawaan ang pagsasalita.", + "tr": "Bugün konuşmanın net ve kolay anlaşılır olup olmadığını test ediyoruz.", + "vi": "Hôm nay chúng tôi kiểm tra xem giọng nói có rõ ràng và dễ hiểu không.", + "zh": "今天我们测试语音是否清晰且容易理解。", +} + +COSY_LANGUAGE = { + "zh": "chinese", + "en": "english", + "ja": "japanese", + "ko": "korean", + "de": "german", + "es": "spanish", + "fr": "french", + "it": "italian", + "ru": "russian", +} + + +@dataclass(frozen=True) +class EngineSpec: + id: str + display_name: str + model_id: str + precision: str + runtime: str + command: str + languages: tuple[str, ...] + benchmark_languages: tuple[str, ...] + requires_language: bool + reference_text_required: bool + + +def registry_platform_key() -> str: + if sys.platform == "darwin": + return "macos" + if sys.platform.startswith("win"): + return "windows" + return "linux" + + +def load_engine_specs(path: Path = REGISTRY_PATH) -> dict[str, EngineSpec]: + registry = json.loads(path.read_text(encoding="utf-8")) + platform = registry_platform_key() + engines: dict[str, EngineSpec] = {} + for raw in registry.get("ttsEngines", []): + item = dict(raw) + if item.get("macosOnly") and platform != "macos": + continue + override = (item.get("platformOverrides") or {}).get(platform) or {} + item.update(override) + engines[item["id"]] = EngineSpec( + id=item["id"], + display_name=item["displayName"], + model_id=item["modelId"], + precision=item["precision"], + runtime=item["runtime"], + command=item["sidecarCommand"], + languages=tuple(item["languages"]), + benchmark_languages=tuple(item.get("benchmarkLanguages") or item["languages"]), + requires_language=bool(item["requiresLanguage"]), + reference_text_required=bool(item["requiresReferenceTranscript"]), + ) + return engines + + +ENGINES: dict[str, EngineSpec] = load_engine_specs() + + +@dataclass +class Case: + engine: EngineSpec + language: str + text: str + + @property + def key(self) -> str: + return f"{self.engine.id}__{self.language}" + + +@dataclass +class Attempt: + case: Case + seed: int + ok: bool = False + error: str = "" + audio_path: str = "" + duration_sec: float = 0.0 + synth_sec: float = 0.0 + sample_rate: int = 0 + transcript: str = "" + asr_sec: float = 0.0 + asr_rtf: float = 0.0 + precision: float = 0.0 + recall: float = 0.0 + wer: float = 1.0 + accuracy: float = 0.0 + pass_intelligibility: bool = False + verdict: str = "failed" + regression: str = "" + metadata: dict[str, Any] = field(default_factory=dict) + + @property + def stem(self) -> str: + return safe_name(f"{self.case.engine.id}__{self.case.language}__s{self.seed}") + + +def safe_name(value: str) -> str: + return re.sub(r"[^A-Za-z0-9_.-]+", "_", value) + + +def run(cmd: list[str], *, timeout: float | None = None) -> subprocess.CompletedProcess[str]: + return subprocess.run( + cmd, + text=True, + stdout=subprocess.PIPE, + stderr=subprocess.STDOUT, + timeout=timeout, + check=False, + ) + + +def ensure_reference(outdir: Path) -> Path: + ref_path = outdir / "ref-samantha.wav" + if ref_path.exists(): + return ref_path + cp = run( + [ + "say", + "-v", + "Samantha", + "-o", + str(ref_path), + "--file-format=WAVE", + "--data-format=LEI16@22050", + REF_TEXT, + ], + timeout=30, + ) + if cp.returncode != 0: + raise RuntimeError(f"failed to generate reference with say:\n{cp.stdout}") + return ref_path + + +class Sidecar: + def __init__(self, binary: Path, log_path: Path): + if not binary.exists(): + raise FileNotFoundError(f"sidecar binary not found: {binary}") + self.log_file = log_path.open("w", encoding="utf-8") + self.proc = subprocess.Popen( + [str(binary)], + cwd=str(ROOT), + stdin=subprocess.PIPE, + stdout=subprocess.PIPE, + stderr=self.log_file, + text=True, + bufsize=1, + ) + self._responses: queue.Queue[str] = queue.Queue() + self._reader = threading.Thread(target=self._read_stdout, daemon=True) + self._reader.start() + + def _read_stdout(self) -> None: + assert self.proc.stdout is not None + for line in self.proc.stdout: + self._responses.put(line) + + def request(self, payload: dict[str, Any], timeout: float) -> dict[str, Any]: + if self.proc.poll() is not None: + raise RuntimeError(f"sidecar exited with code {self.proc.returncode}") + assert self.proc.stdin is not None + self.proc.stdin.write(json.dumps(payload, ensure_ascii=False) + "\n") + self.proc.stdin.flush() + try: + line = self._responses.get(timeout=timeout) + except queue.Empty as exc: + raise TimeoutError(f"sidecar timeout for {payload.get('id')}") from exc + return json.loads(line) + + def close(self) -> None: + if self.proc.poll() is None: + self.proc.terminate() + try: + self.proc.wait(timeout=5) + except subprocess.TimeoutExpired: + self.proc.kill() + self.proc.wait(timeout=5) + self.log_file.close() + + +def target_word_count(text: str) -> int: + tokens = tokenize(text) + return max(1, len(tokens)) + + +def clamp(value: int, lo: int, hi: int) -> int: + return max(lo, min(hi, value)) + + +def language_payload(engine: EngineSpec, language: str, routing: str) -> str | None: + if routing == "production" and not engine.requires_language: + return None + if engine.id == "cosyvoice": + return COSY_LANGUAGE.get(language, language) + if engine.id in {"omnivoice", "indic-mio"} and language == "hi": + return "hindi" + if engine.id == "indic-mio" and language == "en": + return "english" + return language + + +def synthesize( + sidecar: Sidecar, + case: Case, + seed: int, + ref_path: Path, + audio_dir: Path, + routing: str, + timeout: float, +) -> Attempt: + attempt = Attempt(case=case, seed=seed) + lang_dir = audio_dir / case.language + lang_dir.mkdir(parents=True, exist_ok=True) + started = time.monotonic() + words = target_word_count(case.text) + max_tokens = clamp(words * 12 + 40, 60, 320) + min_stop_steps = clamp(words * 5 // 2, 8, max_tokens - 16) + payload: dict[str, Any] = { + "id": attempt.stem, + "command": case.engine.command, + "engine": case.engine.id, + "modelId": case.engine.model_id, + "text": case.text, + "voiceId": f"matrix-{case.engine.id}", + "referenceAudioPath": str(ref_path), + "seed": seed, + "cfgValue": 2.0, + "maxTokens": max_tokens, + "minStopSteps": min_stop_steps, + } + if case.engine.reference_text_required: + payload["referenceText"] = REF_TEXT + language = language_payload(case.engine, case.language, routing) + if language: + payload["language"] = language + attempt.metadata["languageSent"] = language or "" + attempt.metadata["maxTokens"] = max_tokens + attempt.metadata["minStopSteps"] = min_stop_steps + + try: + response = sidecar.request(payload, timeout=timeout) + except Exception as exc: # noqa: BLE001 - preserve error in report + attempt.error = str(exc) + attempt.synth_sec = time.monotonic() - started + return attempt + + attempt.synth_sec = time.monotonic() - started + if response.get("ok") is not True: + attempt.error = str(response.get("error") or "synthesis failed") + return attempt + result = response.get("result") or {} + src = result.get("audioPath") + if not src or not Path(src).exists(): + attempt.error = f"missing output audio: {src}" + return attempt + dest = lang_dir / f"{attempt.stem}.wav" + shutil.copyfile(src, dest) + attempt.audio_path = str(dest) + attempt.duration_sec = float(result.get("durationSec") or 0.0) + attempt.sample_rate = int(result.get("sampleRate") or 0) + attempt.ok = True + return attempt + + +def is_cjk_char(ch: str) -> bool: + code = ord(ch) + return ( + 0x3400 <= code <= 0x4DBF + or 0x4E00 <= code <= 0x9FFF + or 0x3040 <= code <= 0x30FF + or 0xAC00 <= code <= 0xD7AF + ) + + +def normalize_text(text: str) -> str: + text = unicodedata.normalize("NFKC", text).casefold() + out: list[str] = [] + for ch in text: + cat = unicodedata.category(ch) + if cat[0] in {"L", "N", "M"} or is_cjk_char(ch): + out.append(ch) + else: + out.append(" ") + return re.sub(r"\s+", " ", "".join(out)).strip() + + +def tokenize(text: str) -> list[str]: + normalized = normalize_text(text) + if not normalized: + return [] + cjk_count = sum(1 for ch in normalized if is_cjk_char(ch)) + if cjk_count >= max(2, len(normalized.replace(" ", "")) // 3): + return [ch for ch in normalized if not ch.isspace()] + return normalized.split() + + +def edit_distance(a: list[str], b: list[str]) -> int: + prev = list(range(len(b) + 1)) + for i, x in enumerate(a, 1): + cur = [i] + for j, y in enumerate(b, 1): + cur.append( + min( + prev[j] + 1, + cur[j - 1] + 1, + prev[j - 1] + (0 if x == y else 1), + ) + ) + prev = cur + return prev[-1] + + +def score(reference: str, hypothesis: str) -> tuple[float, float, float, float]: + ref = tokenize(reference) + hyp = tokenize(hypothesis) + if not ref: + return 0.0, 0.0, 1.0, 0.0 + overlap = sum((Counter(ref) & Counter(hyp)).values()) + precision = overlap / len(hyp) if hyp else 0.0 + recall = overlap / len(ref) + wer = edit_distance(ref, hyp) / len(ref) + accuracy = max(0.0, 1.0 - wer) + return precision, recall, wer, accuracy + + +def classify_intelligibility(attempt: Attempt) -> str: + if not attempt.ok or attempt.error or not attempt.transcript.strip(): + return "failed" + if attempt.precision >= 0.90 and attempt.recall >= 0.90 and attempt.wer <= 0.15: + return "exact" + if attempt.pass_intelligibility: + return "intelligible" + if attempt.precision >= 0.45 and attempt.recall >= 0.40 and attempt.accuracy >= 0.25: + return "word-drift" + return "failed" + + +def parse_asr_jsonl(stdout: str) -> dict[str, dict[str, Any]]: + out: dict[str, dict[str, Any]] = {} + for line in stdout.splitlines(): + line = line.strip() + if not line.startswith("{"): + continue + try: + item = json.loads(line) + except json.JSONDecodeError: + continue + if "file" in item: + out[str(item["file"])] = item + return out + + +def transcribe_by_language( + attempts: list[Attempt], + audio_dir: Path, + asr_dir: Path, + asr_engine: str, + asr_model: str, +) -> None: + by_lang: dict[str, list[Attempt]] = defaultdict(list) + for attempt in attempts: + if attempt.ok and attempt.audio_path: + by_lang[attempt.case.language].append(attempt) + + for language, items in sorted(by_lang.items()): + lang_audio_dir = audio_dir / language + lang_asr_dir = asr_dir / language + lang_asr_dir.mkdir(parents=True, exist_ok=True) + cmd = [ + "speech", + "transcribe-batch", + str(lang_audio_dir), + "--output-dir", + str(lang_asr_dir), + "--engine", + asr_engine, + "--language", + language, + "--jsonl", + ] + if asr_engine == "qwen3": + cmd.extend(["--model", asr_model]) + started = time.monotonic() + cp = run(cmd) + elapsed = time.monotonic() - started + if cp.returncode != 0: + for item in items: + item.error = item.error or f"ASR failed for language {language}: {cp.stdout[-500:]}" + item.verdict = classify_intelligibility(item) + continue + parsed = parse_asr_jsonl(cp.stdout) + for item in items: + row = parsed.get(item.stem) + if not row: + item.error = item.error or f"ASR missing result for {item.stem}" + item.verdict = classify_intelligibility(item) + continue + item.transcript = str(row.get("text") or "").strip() + item.asr_sec = float(row.get("time") or 0.0) + item.asr_rtf = float(row.get("rtf") or 0.0) + item.metadata["asrBatchWallSec"] = elapsed + p, r, wer, acc = score(item.case.text, item.transcript) + item.precision = p + item.recall = r + item.wer = wer + item.accuracy = acc + item.pass_intelligibility = ( + item.precision >= 0.55 + and item.recall >= 0.60 + and item.accuracy >= 0.45 + ) + item.verdict = classify_intelligibility(item) + + +def select_cases(models: list[str], languages: list[str]) -> list[Case]: + selected_engines = ENGINES.keys() if models == ["all"] else models + cases: list[Case] = [] + for engine_id in selected_engines: + if engine_id not in ENGINES: + raise ValueError(f"unknown engine {engine_id}; choose {', '.join(ENGINES)}") + engine = ENGINES[engine_id] + selected_langs = ( + engine.benchmark_languages if languages == ["all"] else tuple(languages) + ) + for language in selected_langs: + if language not in engine.languages: + continue + if language not in TEXTS: + raise ValueError(f"missing test text for language {language}") + cases.append(Case(engine=engine, language=language, text=TEXTS[language])) + return cases + + +def asr_model_descriptor(asr_engine: str, asr_model: str) -> tuple[str, str]: + if asr_engine == "qwen3": + model_ids = { + "0.6B": ("aufklarer/Qwen3-ASR-0.6B-MLX-4bit", "4bit"), + "0.6B-8bit": ("aufklarer/Qwen3-ASR-0.6B-MLX-8bit", "8bit"), + "1.7B": ("aufklarer/Qwen3-ASR-1.7B-MLX-8bit", "8bit"), + "1.7B-4bit": ("aufklarer/Qwen3-ASR-1.7B-MLX-4bit", "4bit"), + } + return model_ids.get(asr_model, (asr_model, "unknown")) + if asr_engine == "parakeet": + return ("aufklarer/Parakeet-TDT-v3-CoreML-INT8-30s", "int8") + return (asr_model or asr_engine, "unknown") + + +def write_reports( + attempts: list[Attempt], + outdir: Path, + baseline: dict[str, Any] | None, + asr_engine: str, + asr_model: str, +) -> None: + asr_model_id, asr_precision = asr_model_descriptor(asr_engine, asr_model) + rows = [] + for attempt in attempts: + key = f"{attempt.case.engine.id}/{attempt.case.language}" + tts_rtf = ( + attempt.synth_sec / attempt.duration_sec + if attempt.ok and attempt.duration_sec > 0 + else 0.0 + ) + if baseline and key in baseline: + base_acc = float(baseline[key].get("accuracy") or 0.0) + delta = attempt.accuracy - base_acc + if delta <= -0.15: + attempt.regression = f"regressed {delta * 100:.0f}pp" + else: + attempt.regression = f"{delta * 100:+.0f}pp" + rows.append( + { + "engine": attempt.case.engine.id, + "displayName": attempt.case.engine.display_name, + "modelId": attempt.case.engine.model_id, + "modelPrecision": attempt.case.engine.precision, + "runtime": attempt.case.engine.runtime, + "language": attempt.case.language, + "languageSent": attempt.metadata.get("languageSent", ""), + "seed": attempt.seed, + "ok": attempt.ok, + "pass": attempt.pass_intelligibility, + "verdict": attempt.verdict, + "precision": round(attempt.precision, 4), + "recall": round(attempt.recall, 4), + "wer": round(attempt.wer, 4), + "accuracy": round(attempt.accuracy, 4), + "durationSec": round(attempt.duration_sec, 3), + "synthSec": round(attempt.synth_sec, 3), + "ttsRtf": round(tts_rtf, 4), + "asrSec": round(attempt.asr_sec, 3), + "asrRtf": round(attempt.asr_rtf, 4), + "asrEngine": asr_engine, + "asrModel": asr_model, + "asrModelId": asr_model_id, + "asrPrecision": asr_precision, + "audioPath": attempt.audio_path, + "target": attempt.case.text, + "transcript": attempt.transcript, + "error": attempt.error, + "regression": attempt.regression, + } + ) + + csv_path = outdir / "tts-roundtrip-matrix.csv" + with csv_path.open("w", encoding="utf-8", newline="") as f: + writer = csv.DictWriter(f, fieldnames=list(rows[0].keys()) if rows else []) + writer.writeheader() + writer.writerows(rows) + + json_path = outdir / "tts-roundtrip-matrix.json" + json_path.write_text(json.dumps(rows, ensure_ascii=False, indent=2), encoding="utf-8") + + summary: dict[str, Any] = {} + for engine_id in ENGINES: + engine_rows = [r for r in rows if r["engine"] == engine_id] + if not engine_rows: + continue + warm_rows = engine_rows[1:] if len(engine_rows) > 1 else engine_rows + verdict_counts = Counter(str(r["verdict"]) for r in engine_rows) + summary[engine_id] = { + "modelId": ENGINES[engine_id].model_id, + "precision": ENGINES[engine_id].precision, + "runtime": ENGINES[engine_id].runtime, + "cases": len(engine_rows), + "passed": sum(1 for r in engine_rows if r["pass"]), + "passRate": sum(1 for r in engine_rows if r["pass"]) / len(engine_rows), + "verdicts": { + "exact": verdict_counts.get("exact", 0), + "intelligible": verdict_counts.get("intelligible", 0), + "word-drift": verdict_counts.get("word-drift", 0), + "failed": verdict_counts.get("failed", 0), + }, + "meanPrecision": sum(float(r["precision"]) for r in engine_rows) / len(engine_rows), + "meanRecall": sum(float(r["recall"]) for r in engine_rows) / len(engine_rows), + "meanWer": sum(float(r["wer"]) for r in engine_rows) / len(engine_rows), + "meanTtsRtf": sum(float(r["ttsRtf"]) for r in engine_rows) / len(engine_rows), + "warmMeanTtsRtf": sum(float(r["ttsRtf"]) for r in warm_rows) / len(warm_rows), + "meanAsrRtf": sum(float(r["asrRtf"]) for r in engine_rows) / len(engine_rows), + "exactLanguages": [r["language"] for r in engine_rows if r["verdict"] == "exact"], + "intelligibleLanguages": [ + r["language"] for r in engine_rows if r["verdict"] == "intelligible" + ], + "wordDriftLanguages": [ + r["language"] for r in engine_rows if r["verdict"] == "word-drift" + ], + "failedLanguages": [ + r["language"] for r in engine_rows if r["verdict"] == "failed" + ], + "failures": [ + f"{r['language']} acc={float(r['accuracy']) * 100:.0f}% p={float(r['precision']) * 100:.0f}%" + for r in engine_rows + if r["verdict"] == "failed" + ], + "languageResults": "; ".join( + f"{r['language']} {r['verdict']} " + f"P{float(r['precision']) * 100:.0f} " + f"R{float(r['recall']) * 100:.0f} " + f"WER{float(r['wer']) * 100:.0f}" + for r in engine_rows + ), + } + (outdir / "tts-roundtrip-summary.json").write_text( + json.dumps(summary, ensure_ascii=False, indent=2), + encoding="utf-8", + ) + + md = [ + "# TTS Roundtrip Matrix", + "", + f"Generated: {dt.datetime.now().isoformat(timespec='seconds')}", + "", + "Scores are ASR-derived intelligibility proxies: precision/recall are token overlap; WER is edit distance over normalized tokens or CJK characters.", + f"ASR scorer: `{asr_engine}` `{asr_model}` -> `{asr_model_id}` ({asr_precision}).", + "TTS RTF is wall-clock synthesis seconds divided by generated audio seconds. Warm RTF excludes the first row per engine because the sidecar loads that model lazily on first synthesis.", + "Verdicts: `exact` is a high-overlap transcript; `intelligible` passes the regression threshold with minor wording drift; `word-drift` is related/understandable but not exact enough for a pass; `failed` is empty, unintelligible, wrong-language, or unrelated output.", + "", + "| Engine | TTS artifact | Model precision | Roundtrip per language | Verdicts E/I/D/F | Cases | Passed | Pass rate | Mean ASR precision | Mean recall | Mean WER | TTS RTF | Warm TTS RTF | ASR RTF |", + "|---|---|---|---|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|", + ] + for engine_id, item in summary.items(): + md.append( + "| {engine} | `{model}` | {model_precision} | {language_results} | {verdicts} | {cases} | {passed} | {pass_rate:.0%} | {precision:.0%} | {recall:.0%} | {wer:.0%} | {tts_rtf:.2f} | {warm_tts_rtf:.2f} | {asr_rtf:.2f} |".format( + engine=ENGINES[engine_id].display_name, + model=item["modelId"], + model_precision=item["precision"], + language_results=item["languageResults"], + verdicts="{exact}/{intelligible}/{drift}/{failed}".format( + exact=item["verdicts"]["exact"], + intelligible=item["verdicts"]["intelligible"], + drift=item["verdicts"]["word-drift"], + failed=item["verdicts"]["failed"], + ), + cases=item["cases"], + passed=item["passed"], + pass_rate=item["passRate"], + precision=item["meanPrecision"], + recall=item["meanRecall"], + wer=item["meanWer"], + tts_rtf=item["meanTtsRtf"], + warm_tts_rtf=item["warmMeanTtsRtf"], + asr_rtf=item["meanAsrRtf"], + ) + ) + md.extend( + [ + "", + "## Per Case", + "", + "| Engine | Model precision | Lang | Sent | Verdict | Pass | ASR precision | Recall | WER | Duration | Synth | TTS RTF | ASR RTF | Transcript | Error |", + "|---|---|---|---|---|---:|---:|---:|---:|---:|---:|---:|---:|---|---|", + ] + ) + for r in rows: + transcript = str(r["transcript"]).replace("|", "\\|") + if len(transcript) > 80: + transcript = transcript[:77] + "..." + error = str(r["error"]).replace("|", "\\|") + if len(error) > 80: + error = error[:77] + "..." + md.append( + "| {engine} | {model_precision} | {lang} | {sent} | {verdict} | {passed} | {precision:.0%} | {recall:.0%} | {wer:.0%} | {duration:.1f}s | {synth:.1f}s | {tts_rtf:.2f} | {asr_rtf:.2f} | {transcript} | {error} |".format( + engine=r["displayName"], + model_precision=r["modelPrecision"], + lang=r["language"], + sent=r["languageSent"] or "-", + verdict=r["verdict"], + passed="yes" if r["pass"] else "no", + precision=float(r["precision"]), + recall=float(r["recall"]), + wer=float(r["wer"]), + duration=float(r["durationSec"]), + synth=float(r["synthSec"]), + tts_rtf=float(r["ttsRtf"]), + asr_rtf=float(r["asrRtf"]), + transcript=transcript, + error=error, + ) + ) + (outdir / "tts-roundtrip-report.md").write_text("\n".join(md) + "\n", encoding="utf-8") + + +def load_baseline(path: Path | None) -> dict[str, Any] | None: + if not path: + return None + rows = json.loads(path.read_text(encoding="utf-8")) + return {f"{row['engine']}/{row['language']}": row for row in rows} + + +def main() -> int: + parser = argparse.ArgumentParser() + parser.add_argument("--models", default="all", help="Comma list or all") + parser.add_argument("--languages", default="all", help="Comma list or all") + parser.add_argument("--outdir", default="") + parser.add_argument("--sidecar", default=str(SIDECAR)) + parser.add_argument("--asr-engine", default="qwen3") + parser.add_argument("--asr-model", default="0.6B") + parser.add_argument("--seed", type=int, default=1000) + parser.add_argument("--timeout-sec", type=float, default=600) + parser.add_argument( + "--routing", + choices=("production", "declared"), + default="production", + help="production sends language only when requiresLanguage=true; declared sends it whenever the model-side API accepts one", + ) + parser.add_argument("--baseline-json", default="") + args = parser.parse_args() + + models = [x.strip() for x in args.models.split(",") if x.strip()] + languages = [x.strip() for x in args.languages.split(",") if x.strip()] + outdir = Path(args.outdir) if args.outdir else Path("/tmp/speech-studio-roundtrip") / dt.datetime.now().strftime("%Y%m%d-%H%M%S") + outdir.mkdir(parents=True, exist_ok=True) + audio_dir = outdir / "audio" + asr_dir = outdir / "asr" + audio_dir.mkdir(exist_ok=True) + asr_dir.mkdir(exist_ok=True) + + cases = select_cases(models, languages) + ref_path = ensure_reference(outdir) + print(f"[matrix] output: {outdir}") + print(f"[matrix] cases: {len(cases)}") + print(f"[matrix] reference: {ref_path}") + + attempts: list[Attempt] = [] + sidecar = Sidecar(Path(args.sidecar), outdir / "sidecar.stderr.log") + try: + for index, case in enumerate(cases, 1): + print( + f"[matrix] synth {index}/{len(cases)} {case.engine.id}/{case.language}", + flush=True, + ) + attempt = synthesize( + sidecar, + case, + args.seed, + ref_path, + audio_dir, + args.routing, + args.timeout_sec, + ) + if attempt.ok: + print( + f" ok {attempt.duration_sec:.2f}s audio in {attempt.synth_sec:.1f}s", + flush=True, + ) + else: + print(f" failed: {attempt.error}", flush=True) + attempts.append(attempt) + finally: + sidecar.close() + + print("[matrix] transcribing by language...", flush=True) + transcribe_by_language(attempts, audio_dir, asr_dir, args.asr_engine, args.asr_model) + write_reports( + attempts, + outdir, + load_baseline(Path(args.baseline_json)) if args.baseline_json else None, + args.asr_engine, + args.asr_model, + ) + + passed = sum(1 for item in attempts if item.pass_intelligibility) + print(f"[matrix] pass: {passed}/{len(attempts)}") + print(f"[matrix] report: {outdir / 'tts-roundtrip-report.md'}") + print(f"[matrix] csv: {outdir / 'tts-roundtrip-matrix.csv'}") + return 0 if passed == len(attempts) else 2 + + +if __name__ == "__main__": + raise SystemExit(main()) diff --git a/src-tauri/Cargo.lock b/src-tauri/Cargo.lock index 900eb7f..4d87ec6 100644 --- a/src-tauri/Cargo.lock +++ b/src-tauri/Cargo.lock @@ -3469,6 +3469,7 @@ dependencies = [ name = "speech-studio" version = "0.0.8" dependencies = [ + "base64 0.22.1", "chrono", "dirs 5.0.1", "serde", diff --git a/src-tauri/Cargo.toml b/src-tauri/Cargo.toml index 2ed3d76..6000552 100644 --- a/src-tauri/Cargo.toml +++ b/src-tauri/Cargo.toml @@ -28,3 +28,4 @@ chrono = { version = "0.4", features = ["serde"] } dirs = "5" tauri-plugin-updater = "2" tauri-plugin-process = "2" +base64 = "0.22" diff --git a/src-tauri/resources/voices/hindi_fleurs.wav b/src-tauri/resources/voices/hindi_fleurs.wav new file mode 100644 index 0000000000000000000000000000000000000000..2251c6391051d894d38b8ac649c2b3439dfa94fa GIT binary patch literal 122924 zcma%j2YeL8+yCC(?q0v-l1neNgain^cLYQQr70pHf;6#U!G?%{g`W)-l_H7?3IZyk zC`ggsdk8I%5E2s7bGcma`=2MzZ{FDp_`d(WPj+UW@_ow8&fd+=X6ysQhGi5hxbgQq zdhe_`uQZS5I8H%6iwBU(TO6n4qPZDQzVakTWd84?sSLCw2@#uWD;hbGRFK63e1Ibo z@oqX)ULprtiqxSf3>$osx6nt5gQffozEFA8q%Ee2{z?+H%_QVVRGv!FlA=N>*Ob@M 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use serde::{Deserialize, Serialize}; +use std::collections::HashMap; use std::io::{BufRead, BufReader, Write}; use std::path::{Path, PathBuf}; use std::process::{Child, ChildStdin, ChildStdout, Command, Stdio}; use std::sync::{ atomic::{AtomicU32, Ordering}, - Mutex, + LazyLock, Mutex, }; +use std::time::Instant; use tauri::{Emitter, Manager, State}; use tauri_plugin_dialog::DialogExt; @@ -382,20 +385,28 @@ enum TtsEngine { FishAudio, } -#[derive(Clone, Copy, Serialize)] +#[derive(Clone, Debug, Deserialize, Serialize)] struct TtsEngineInfo { id: TtsEngine, #[serde(rename = "displayName")] - display_name: &'static str, + display_name: String, #[serde(rename = "modelName")] - model_name: &'static str, + model_name: String, #[serde(rename = "modelId")] - model_id: &'static str, + model_id: String, #[serde(rename = "modelSize")] - model_size: &'static str, - languages: &'static [&'static str], + model_size: String, + runtime: String, + precision: String, + languages: Vec, + #[serde( + rename = "benchmarkLanguages", + default, + skip_serializing_if = "Vec::is_empty" + )] + benchmark_languages: Vec, #[serde(rename = "voiceProfileModes")] - voice_profile_modes: &'static [&'static str], + voice_profile_modes: Vec, #[serde(rename = "requiresReferenceAudio")] requires_reference_audio: bool, #[serde(rename = "requiresReferenceTranscript")] @@ -403,263 +414,183 @@ struct TtsEngineInfo { #[serde(rename = "requiresLanguage")] requires_language: bool, #[serde(rename = "styleMode")] - style_mode: &'static str, + style_mode: String, #[serde(rename = "supportsInstruct")] supports_instruct: bool, #[serde(rename = "supportedMarkers")] - supported_markers: &'static [&'static str], + supported_markers: Vec, #[serde(rename = "needsTrim")] needs_trim: bool, #[serde(rename = "sampleRate")] sample_rate: u32, #[serde(rename = "usePolicy")] - use_policy: &'static str, - readiness: &'static str, + use_policy: String, + readiness: String, } -#[derive(Clone, Copy)] +#[derive(Clone, Debug, Deserialize)] +#[serde(rename_all = "camelCase")] struct TtsEngineRegistryEntry { + #[serde(flatten)] info: TtsEngineInfo, - sidecar_command: &'static str, + sidecar_command: String, macos_only: bool, + #[serde(default)] + platform_overrides: HashMap, } -const REFERENCE_CLONE_PROFILE: &[&str] = &["reference-clone"]; -const EN_ZH_LANGUAGES: &[&str] = &["en", "zh"]; -const QWEN_TTS_LANGUAGES: &[&str] = &["zh", "en", "ja", "ko", "de", "fr", "ru", "pt", "es", "it"]; -const CHATTERBOX_LANGUAGES: &[&str] = &[ - "ar", "da", "de", "el", "en", "es", "fi", "fr", "he", "hi", "it", "ja", "ko", "ms", "nl", "no", - "pl", "pt", "ru", "sv", "sw", "tr", "zh", -]; -const OMNIVOICE_LANGUAGES: &[&str] = &[ - "en", "hi", "ru", "es", "fr", "de", "it", "pt", "zh", "ja", "ko", -]; -const HI_EN_LANGUAGES: &[&str] = &["hi", "en"]; -const INSTRUCTION_MARKERS: &[&str] = &[ - "soft", - "warm", - "whispering", - "intense", - "excited", - "happy", - "calm", - "serious", - "surprised", - "sad", - "angry", - "dramatic", - "laughs", -]; -const OMNIVOICE_MARKERS: &[&str] = &[ - "whispering", - "excited", - "happy", - "calm", - "serious", - "sad", - "angry", -]; -const INDIC_MIO_MARKERS: &[&str] = &["happy", "sad", "angry", "disgust", "fear", "surprise"]; -const FISH_AUDIO_MARKERS: &[&str] = &[ - "pause", - "emphasis", - "laughing", - "excited", - "angry", - "whisper", - "screaming", - "shouting", - "surprised", - "sad", -]; - -const TTS_ENGINE_REGISTRY: &[TtsEngineRegistryEntry] = &[ - TtsEngineRegistryEntry { - info: TtsEngineInfo { - id: TtsEngine::VoxCPM2, - display_name: "VoxCPM2", - model_name: "voxcpm2-mlx-int8", - model_id: "aufklarer/VoxCPM2-MLX-int8", - model_size: "1.7B", - languages: EN_ZH_LANGUAGES, - voice_profile_modes: REFERENCE_CLONE_PROFILE, - requires_reference_audio: true, - requires_reference_transcript: false, - requires_language: false, - style_mode: "instruction", - supports_instruct: true, - supported_markers: INSTRUCTION_MARKERS, - needs_trim: true, - sample_rate: 48_000, - use_policy: "commercial-safe", - readiness: "production", - }, - sidecar_command: "synthesize_voxcpm2", - macos_only: false, - }, - TtsEngineRegistryEntry { - info: TtsEngineInfo { - id: TtsEngine::CosyVoice, - display_name: "CosyVoice 3", - model_name: "cosyvoice-3-0.5b-mlx-bf16", - model_id: "aufklarer/CosyVoice3-0.5B-MLX-bf16", - model_size: "0.5B", - languages: EN_ZH_LANGUAGES, - voice_profile_modes: REFERENCE_CLONE_PROFILE, - requires_reference_audio: true, - requires_reference_transcript: true, - requires_language: false, - style_mode: "instruction", - supports_instruct: true, - supported_markers: INSTRUCTION_MARKERS, - needs_trim: true, - sample_rate: 24_000, - use_policy: "commercial-safe", - readiness: "production", - }, - sidecar_command: "synthesize_cosyvoice", - macos_only: true, - }, - TtsEngineRegistryEntry { - info: TtsEngineInfo { - id: TtsEngine::Qwen3, - display_name: "Qwen3-TTS", - model_name: "qwen3-tts-1.7b-mlx-bf16", - model_id: "aufklarer/Qwen3-TTS-12Hz-1.7B-Base-MLX-bf16", - model_size: "1.7B", - languages: QWEN_TTS_LANGUAGES, - voice_profile_modes: REFERENCE_CLONE_PROFILE, - requires_reference_audio: true, - requires_reference_transcript: true, - requires_language: false, - style_mode: "none", - supports_instruct: false, - supported_markers: &[], - needs_trim: true, - sample_rate: 24_000, - use_policy: "commercial-safe", - readiness: "legacy-fallback", - }, - sidecar_command: "synthesize_icl", - macos_only: true, - }, - TtsEngineRegistryEntry { - info: TtsEngineInfo { - id: TtsEngine::Chatterbox, - display_name: "Chatterbox", - model_name: "chatterbox-multilingual-mlx-fp16", - model_id: "aufklarer/Chatterbox-Multilingual-MLX-fp16", - model_size: "0.5B", - languages: CHATTERBOX_LANGUAGES, - voice_profile_modes: REFERENCE_CLONE_PROFILE, - requires_reference_audio: true, - requires_reference_transcript: false, - requires_language: true, - style_mode: "intensity", - supports_instruct: false, - supported_markers: INSTRUCTION_MARKERS, - needs_trim: true, - sample_rate: 24_000, - use_policy: "commercial-safe", - readiness: "production", - }, - sidecar_command: "synthesize_chatterbox", - macos_only: true, - }, - TtsEngineRegistryEntry { - info: TtsEngineInfo { - id: TtsEngine::OmniVoice, - display_name: "OmniVoice", - model_name: "omnivoice-mlx-int8", - model_id: "aufklarer/OmniVoice-MLX-int8", - model_size: "0.5B", - languages: OMNIVOICE_LANGUAGES, - voice_profile_modes: REFERENCE_CLONE_PROFILE, - requires_reference_audio: true, - requires_reference_transcript: false, - requires_language: true, - style_mode: "controlled-vocabulary", - supports_instruct: false, - supported_markers: OMNIVOICE_MARKERS, - needs_trim: true, - sample_rate: 24_000, - use_policy: "commercial-safe", - readiness: "production", - }, - sidecar_command: "synthesize_omnivoice", - macos_only: true, - }, - TtsEngineRegistryEntry { - info: TtsEngineInfo { - id: TtsEngine::IndicMio, - display_name: "Indic-Mio", - model_name: "indic-mio-mlx-fp16", - model_id: "aufklarer/Indic-Mio-MLX-fp16", - model_size: "0.6B", - languages: HI_EN_LANGUAGES, - voice_profile_modes: REFERENCE_CLONE_PROFILE, - requires_reference_audio: true, - requires_reference_transcript: false, - requires_language: false, - style_mode: "suffix-tag", - supports_instruct: false, - supported_markers: INDIC_MIO_MARKERS, - needs_trim: true, - sample_rate: 24_000, - use_policy: "commercial-safe", - readiness: "production", - }, - sidecar_command: "synthesize_indic_mio", - macos_only: true, - }, - TtsEngineRegistryEntry { - info: TtsEngineInfo { - id: TtsEngine::FishAudio, - display_name: "Fish Audio S2 Pro", - model_name: "fish-audio-s2-pro-mlx-fp16", - model_id: "aufklarer/Fish-Audio-S2-Pro-MLX-fp16", - model_size: "S2 Pro", - languages: HI_EN_LANGUAGES, - voice_profile_modes: REFERENCE_CLONE_PROFILE, - requires_reference_audio: true, - requires_reference_transcript: true, - requires_language: false, - style_mode: "bracket-tag", - supports_instruct: false, - supported_markers: FISH_AUDIO_MARKERS, - needs_trim: false, - sample_rate: 44_100, - use_policy: "research-only", - readiness: "benchmark", - }, - sidecar_command: "synthesize_fish_audio", - macos_only: true, - }, -]; +#[derive(Clone, Copy, Debug, Deserialize, Serialize, PartialEq, Eq)] +#[serde(rename_all = "kebab-case")] +enum AsrModel { + ParakeetTdtV3, +} + +#[derive(Clone, Debug, Deserialize, Serialize)] +struct AsrModelInfo { + id: AsrModel, + #[serde(rename = "displayName")] + display_name: String, + #[serde(rename = "modelName")] + model_name: String, + #[serde(rename = "modelId")] + model_id: String, + #[serde(rename = "modelSize")] + model_size: String, + languages: Vec, + runtime: String, + #[serde(rename = "sampleRate")] + sample_rate: u32, + #[serde(rename = "maxSegmentSec")] + max_segment_sec: u32, + streaming: bool, + readiness: String, +} + +#[derive(Clone, Debug, Deserialize)] +#[serde(rename_all = "camelCase")] +struct AsrModelRegistryEntry { + #[serde(flatten)] + info: AsrModelInfo, + sidecar_command: String, + #[serde(default)] + platform_overrides: HashMap, +} + +#[derive(Clone, Debug, Default, Deserialize)] +#[serde(rename_all = "camelCase")] +struct ModelPlatformOverride { + model_name: Option, + model_id: Option, + runtime: Option, + precision: Option, +} + +#[derive(Clone, Debug, Deserialize)] +#[serde(rename_all = "camelCase")] +struct ModelRegistry { + version: u32, + tts_engines: Vec, + asr_models: Vec, +} + +impl TtsEngineInfo { + fn apply_platform_override(&mut self, item: &ModelPlatformOverride) { + if let Some(value) = &item.model_name { + self.model_name = value.clone(); + } + if let Some(value) = &item.model_id { + self.model_id = value.clone(); + } + if let Some(value) = &item.runtime { + self.runtime = value.clone(); + } + if let Some(value) = &item.precision { + self.precision = value.clone(); + } + } +} + +impl AsrModelInfo { + fn apply_platform_override(&mut self, item: &ModelPlatformOverride) { + if let Some(value) = &item.model_name { + self.model_name = value.clone(); + } + if let Some(value) = &item.model_id { + self.model_id = value.clone(); + } + if let Some(value) = &item.runtime { + self.runtime = value.clone(); + } + } +} + +fn platform_registry_key() -> &'static str { + if cfg!(target_os = "macos") { + "macos" + } else if cfg!(target_os = "windows") { + "windows" + } else { + "linux" + } +} + +static MODEL_REGISTRY: LazyLock = LazyLock::new(|| { + let mut registry: ModelRegistry = + serde_json::from_str(include_str!("../../model-registry.json")) + .expect("model-registry.json must be valid"); + assert_eq!(registry.version, 1, "unsupported model registry version"); + + let platform = platform_registry_key(); + for entry in &mut registry.tts_engines { + if let Some(item) = entry.platform_overrides.get(platform) { + entry.info.apply_platform_override(item); + } + } + for entry in &mut registry.asr_models { + if let Some(item) = entry.platform_overrides.get(platform) { + entry.info.apply_platform_override(item); + } + } + registry +}); + +impl AsrModel { + fn registry_entry(self) -> &'static AsrModelRegistryEntry { + MODEL_REGISTRY + .asr_models + .iter() + .find(|entry| entry.info.id == self) + .expect("AsrModel missing from ASR_MODEL_REGISTRY") + } + + fn sidecar_command(self) -> &'static str { + self.registry_entry().sidecar_command.as_str() + } +} impl TtsEngine { fn registry_entry(self) -> &'static TtsEngineRegistryEntry { - TTS_ENGINE_REGISTRY + MODEL_REGISTRY + .tts_engines .iter() .find(|entry| entry.info.id == self) .expect("TtsEngine missing from TTS_ENGINE_REGISTRY") } fn sidecar_command(self) -> &'static str { - self.registry_entry().sidecar_command + self.registry_entry().sidecar_command.as_str() } fn display_name(self) -> &'static str { - self.registry_entry().info.display_name + self.registry_entry().info.display_name.as_str() } fn requires_reference_transcript(self) -> bool { self.registry_entry().info.requires_reference_transcript } - /// Whether synthesis needs a caller-chosen language. Chatterbox prepends a - /// `[lang]` token, so the Studio shows a language picker for it; the other - /// engines infer language from the text. + /// Whether synthesis needs a caller-chosen language. The Studio shows a + /// language picker only for engines that declare this in the registry. fn requires_language(self) -> bool { self.registry_entry().info.requires_language } @@ -673,13 +604,25 @@ impl TtsEngine { /// - `bracket-tag`: marker is appended as an engine-specific bracket tag. /// - `none`: markers are stripped and ignored. fn style_mode(self) -> &'static str { - self.registry_entry().info.style_mode + self.registry_entry().info.style_mode.as_str() } } fn normalize_sidecar_language(engine: TtsEngine, language: Option<&str>) -> Option { let trimmed = language.map(str::trim).filter(|value| !value.is_empty()); match engine { + TtsEngine::CosyVoice => trimmed.map(|value| match value.to_ascii_lowercase().as_str() { + "zh" | "zho" | "cmn" | "chinese" => "chinese".to_string(), + "en" | "eng" | "english" => "english".to_string(), + "ja" | "jpn" | "japanese" => "japanese".to_string(), + "ko" | "kor" | "korean" => "korean".to_string(), + "de" | "deu" | "ger" | "german" => "german".to_string(), + "es" | "spa" | "spanish" => "spanish".to_string(), + "fr" | "fra" | "fre" | "french" => "french".to_string(), + "it" | "ita" | "italian" => "italian".to_string(), + "ru" | "rus" | "russian" => "russian".to_string(), + _ => value.to_string(), + }), // The UI keeps BCP-47-ish ids because Chatterbox expects `[hi]`, but // OmniVoice gives cleaner Hindi output with the spelled language item. TtsEngine::OmniVoice | TtsEngine::IndicMio => { @@ -732,15 +675,29 @@ fn humanize_sidecar_error(engine: TtsEngine, error: String) -> String { } fn tts_engine_info(engine: TtsEngine) -> TtsEngineInfo { - engine.registry_entry().info + engine.registry_entry().info.clone() +} + +fn asr_model_info(model: AsrModel) -> AsrModelInfo { + model.registry_entry().info.clone() } #[tauri::command] async fn available_tts_engines() -> Vec { - TTS_ENGINE_REGISTRY + MODEL_REGISTRY + .tts_engines .iter() .filter(|entry| engine_is_supported(entry.info.id)) - .map(|entry| entry.info) + .map(|entry| entry.info.clone()) + .collect() +} + +#[tauri::command] +async fn available_asr_models() -> Vec { + MODEL_REGISTRY + .asr_models + .iter() + .map(|entry| entry.info.clone()) .collect() } @@ -762,10 +719,12 @@ struct InitModelArgs { #[tauri::command] async fn init_model(manager: State<'_, SidecarManager>, args: InitModelArgs) -> Result<(), String> { ensure_engine_supported(args.engine)?; + let info = tts_engine_info(args.engine); let payload = serde_json::json!({ "id": format!("init-{}", uuid::Uuid::new_v4()), "command": "init_model", "engine": args.engine, + "modelId": info.model_id, }); let raw = manager.request(&payload)?; let env: SidecarResponse = serde_json::from_value(raw).map_err(|e| e.to_string())?; @@ -870,9 +829,7 @@ fn reference_access_error(action: &str, path: &Path, err: &std::io::Error) -> St std::io::ErrorKind::NotFound => { "The file is no longer at that path. Re-add the reference from its current location." } - _ => { - "Copy or export the reference audio to a normal local folder, then add it again." - } + _ => "Copy or export the reference audio to a normal local folder, then add it again.", }; format!( "Cannot {action} reference audio \"{}\": {err}. {hint}", @@ -1116,8 +1073,8 @@ struct SynthesizeArgs { reference_audio_path: String, #[serde(rename = "referenceText")] reference_text: String, - /// Synthesis language id (Chatterbox `[lang]` token, e.g. "en"/"ar"/"hi"). - /// Optional; engines that infer language from text ignore it. + /// Synthesis language id for engines with `requiresLanguage=true`. + /// Optional; engines that infer or default language do not receive it. #[serde(default)] language: Option, } @@ -1268,6 +1225,25 @@ fn chunk_text_for_synthesis(text: &str, max_words: usize) -> Vec { chunks } +const DEFAULT_SYNTH_SEED_LADDER: &[u64] = &[1000, 1001, 1002, 1010, 1011, 1012]; + +fn synth_seed_ladder(engine: TtsEngine) -> &'static [u64] { + debug_assert_ne!(engine, TtsEngine::Qwen3); + DEFAULT_SYNTH_SEED_LADDER +} + +fn synth_max_tokens(engine: TtsEngine, target_word_count: usize) -> usize { + if engine == TtsEngine::Qwen3 { + // Qwen3 frames are ~80 ms each. The generic cap lets short lines run + // to 96 frames (~7.7 s of audio, ~12 s wall time) whenever EOS fails. + // Keep enough headroom for slow speech, but prevent minute-long retry + // ladders for one short utterance. + (target_word_count.saturating_mul(4) + 20).clamp(40, 96) + } else { + (target_word_count.saturating_mul(12) + 40).clamp(60, 320) + } +} + /// One synthesis pass (seed/cfg retry ladder + optional ASR grading) for a /// single piece of text. Returns (audio_path, duration_sec) of the accepted /// take. Extracted from synthesize_clip so long-form chunking can call it @@ -1285,15 +1261,12 @@ fn synth_one_line( invocation_salt: &str, part_idx: usize, ) -> Result<(String, f64), String> { - // Seed ladder: both backends are deterministic per seed. VoxCPM2 also - // consumes cfgValue; CosyVoice ignores that optional field. - const SEED_LADDER: &[u64] = &[1000, 1001, 1002, 1010, 1011, 1012]; const CFG_LADDER: &[f32] = &[2.0, 2.5, 3.0]; // Token budget: ~12 steps/word + headroom (each step ≈ 50 ms of audio). let grade_target = strip_style_markers_for_grading(text); let target_word_count = canon_tokens(&grade_target).len(); - let max_tokens = (target_word_count.saturating_mul(12) + 40).clamp(60, 320); + let max_tokens = synth_max_tokens(engine, target_word_count); // Floor under the model's stop signal: VoxCPM2 fires its stop token // prematurely on long non-Latin-script lines (a 19-word Hindi sentence // stops at ~40 steps ≈ 6 s, cutting the sentence). The model speaks @@ -1314,16 +1287,59 @@ fn synth_one_line( .chars() .any(|c| !c.is_ascii() && c.is_alphabetic()); let sidecar_language = normalize_sidecar_language(engine, language); + let model_id = engine.registry_entry().info.model_id.as_str(); let mut best: Option<(String, Grade, u64, f64)> = None; let mut last_error: Option = None; - for (attempt_idx, &seed) in SEED_LADDER.iter().enumerate() { + if engine == TtsEngine::Qwen3 { + let seed = 1000; + let payload = serde_json::json!({ + "id": format!("synth-{}-p{}-s{}-{}", clip_id, part_idx, seed, invocation_salt), + "command": engine.sidecar_command(), + "engine": engine, + "modelId": model_id, + "text": text, + "voiceId": voice_id, + "referenceAudioPath": reference_audio_path, + "referenceText": reference_text, + "language": sidecar_language.as_deref(), + "seed": seed, + "maxTokens": max_tokens, + }); + let raw = manager.request(&payload)?; + let env: SidecarResponse = serde_json::from_value(raw).map_err(|e| e.to_string())?; + if !env.ok { + return Err(humanize_sidecar_error( + engine, + env.error.unwrap_or_else(|| "sidecar error".into()), + )); + } + let result = env.result.unwrap_or_default(); + let audio_path = result + .get("audioPath") + .and_then(|v| v.as_str()) + .ok_or_else(|| "missing audioPath in sidecar response".to_string())? + .to_string(); + let duration = result + .get("durationSec") + .and_then(|v| v.as_f64()) + .unwrap_or(0.0); + validate_synth_audio(&audio_path)?; + eprintln!( + "[synth] clip {} part {} accepted qwen single-shot (seed={}, {:.2}s)", + clip_id, part_idx, seed, duration + ); + return Ok((audio_path, duration)); + } + + for (attempt_idx, &seed) in synth_seed_ladder(engine).iter().enumerate() { let cfg = CFG_LADDER[attempt_idx.min(CFG_LADDER.len() - 1)]; let payload = serde_json::json!({ "id": format!("synth-{}-p{}-s{}-{}", clip_id, part_idx, seed, invocation_salt), "command": engine.sidecar_command(), "engine": engine, + "modelId": model_id, "text": text, "voiceId": voice_id, "referenceAudioPath": reference_audio_path, @@ -2450,11 +2466,9 @@ fn canon_tokens(s: &str) -> Vec { // ---------- demo seed ---------- // -// The demo uses real Qwen3-TTS ICL synthesis. Since Qwen3-TTS needs a -// reference audio + reference transcript per voice, and we don't ship any -// audio in this repo, we bootstrap the references by calling macOS `say` -// (Samantha / Daniel) into a temp WAV. Then we synthesize each demo line -// through the sidecar, which loads the Qwen3-TTS model on first call. +// The demo embeds human reference WAVs. Engines such as Qwen3-TTS and Fish +// Audio need the reference transcript to match that WAV closely, otherwise +// prompt words can leak into the synthesized take. // // First-ever invocation: downloads ~300MB of model weights from HuggingFace, // then ~2-5s per line. Subsequent invocations reuse the warm model. @@ -2487,6 +2501,9 @@ struct DemoSeed { clips: Vec, } +const DEMO_ANNA_REFERENCE_TEXT: &str = "The Hispaniola was rolling scuppers under in the ocean swell. The booms were tearing at the blocks. The rudder was banging."; +const DEMO_MAREK_REFERENCE_TEXT: &str = "It is a pretty little spot there, a green grass plateau running along by the water's edge and overhung by willows."; + fn short_hash(s: &str) -> u32 { // FNV-1a 32-bit. Stable across runs without pulling another crate. let mut h: u32 = 0x811c9dc5; @@ -2511,6 +2528,15 @@ fn clip_cache_dir() -> std::path::PathBuf { dir } +fn dictation_cache_dir() -> std::path::PathBuf { + let dir = dirs::cache_dir() + .unwrap_or_else(std::env::temp_dir) + .join("audio.soniqo.studio") + .join("dictation"); + let _ = std::fs::create_dir_all(&dir); + dir +} + fn wav_duration_sec(path: &std::path::Path) -> Result { use std::io::Read; let mut f = std::fs::File::open(path).map_err(|e| e.to_string())?; @@ -2528,6 +2554,132 @@ fn wav_duration_sec(path: &std::path::Path) -> Result { Ok(audio_bytes as f64 / byte_rate as f64) } +#[derive(Deserialize)] +struct SaveDictationAudioArgs { + #[serde(rename = "wavBase64")] + wav_base64: String, +} + +#[derive(Serialize)] +struct SaveDictationAudioResult { + #[serde(rename = "audioPath")] + audio_path: String, + #[serde(rename = "durationSec")] + duration_sec: f64, +} + +#[tauri::command] +async fn save_dictation_audio( + args: SaveDictationAudioArgs, +) -> Result { + let bytes = base64::engine::general_purpose::STANDARD + .decode(args.wav_base64.trim()) + .map_err(|e| format!("invalid dictation audio payload: {e}"))?; + const MAX_DICTATION_WAV_BYTES: usize = 100 * 1024 * 1024; + if bytes.len() > MAX_DICTATION_WAV_BYTES { + return Err("dictation recording is too large".into()); + } + if bytes.len() < 44 || &bytes[0..4] != b"RIFF" || &bytes[8..12] != b"WAVE" { + return Err("dictation audio must be a WAV file".into()); + } + + let path = + dictation_cache_dir().join(format!("dictation-{}.wav", uuid::Uuid::new_v4().simple())); + std::fs::write(&path, &bytes).map_err(|e| format!("could not write dictation audio: {e}"))?; + let duration_sec = wav_duration_sec(&path).unwrap_or(0.0); + Ok(SaveDictationAudioResult { + audio_path: path.to_string_lossy().to_string(), + duration_sec, + }) +} + +#[derive(Deserialize)] +struct TranscribeAudioArgs { + #[serde(rename = "audioPath")] + audio_path: String, + model: Option, + language: Option, +} + +#[derive(Serialize)] +struct TranscribeAudioResult { + text: String, + #[serde(rename = "modelName")] + model_name: String, + #[serde(rename = "modelId")] + model_id: String, + #[serde(rename = "durationSec")] + duration_sec: f64, + #[serde(rename = "elapsedSec")] + elapsed_sec: f64, + #[serde(skip_serializing_if = "Option::is_none")] + language: Option, +} + +#[tauri::command] +async fn transcribe_audio( + manager: State<'_, SidecarManager>, + args: TranscribeAudioArgs, +) -> Result { + let model = args.model.unwrap_or(AsrModel::ParakeetTdtV3); + let info = asr_model_info(model); + let audio_path = PathBuf::from(&args.audio_path); + let metadata = std::fs::metadata(&audio_path) + .map_err(|e| format!("cannot read dictation audio {}: {e}", audio_path.display()))?; + if !metadata.is_file() { + return Err(format!( + "dictation audio path is not a file: {}", + audio_path.display() + )); + } + + let started = Instant::now(); + let payload = serde_json::json!({ + "id": format!("asr-{}", uuid::Uuid::new_v4().simple()), + "command": model.sidecar_command(), + "audioPath": audio_path.to_string_lossy(), + "language": args.language, + }); + let raw = manager.request(&payload)?; + let env: SidecarResponse = serde_json::from_value(raw).map_err(|e| e.to_string())?; + if !env.ok { + return Err(env + .error + .unwrap_or_else(|| format!("{} transcription failed", info.display_name))); + } + + let result = env.result.unwrap_or_default(); + let text = result + .get("text") + .and_then(|v| v.as_str()) + .unwrap_or("") + .trim() + .to_string(); + let language = result + .get("language") + .and_then(|v| v.as_str()) + .filter(|value| !value.is_empty()) + .map(str::to_string); + let duration_sec = result + .get("durationSec") + .and_then(|v| v.as_f64()) + .or_else(|| wav_duration_sec(&audio_path).ok()) + .unwrap_or(0.0); + let elapsed_sec = result + .get("elapsedSec") + .and_then(|v| v.as_f64()) + .unwrap_or_else(|| started.elapsed().as_secs_f64()); + + Ok(TranscribeAudioResult { + text, + model_name: info.model_name, + model_id: info.model_id, + duration_sec, + elapsed_sec, + language, + }) +} + #[derive(Serialize, Clone)] struct DemoProgress { phase: &'static str, @@ -2554,9 +2706,38 @@ fn emit_progress( ); } +fn demo_clip_seeds(cache_prefix: &str, lines: &[(usize, &str)]) -> Vec { + let cache_dir = clip_cache_dir(); + let mut clips = Vec::with_capacity(lines.len()); + for (idx, (speaker_idx, text)) in lines.iter().enumerate() { + let stable_id = format!( + "{}-s{}-l{}-{:x}", + cache_prefix, + speaker_idx, + idx, + short_hash(text) + ); + let cached_path = cache_dir.join(format!("{}.wav", stable_id)); + let (audio_path, duration_sec) = if cached_path.exists() { + let dur = wav_duration_sec(&cached_path).ok(); + (Some(cached_path.to_string_lossy().to_string()), dur) + } else { + (None, None) + }; + + clips.push(DemoClipSeed { + speaker_index: *speaker_idx, + audio_path, + duration_sec, + text: (*text).to_string(), + }); + } + clips +} + #[tauri::command] async fn seed_demo(app: tauri::AppHandle) -> Result { - eprintln!("[seed_demo] start (lazy mode: no Qwen3 synth, only `say` references)"); + eprintln!("[seed_demo] start (lazy mode: bundled references only)"); emit_progress(&app, "references", 0, 1, "Preparing reference voices…"); let dir = std::env::temp_dir().join("soniqo-demo"); std::fs::create_dir_all(&dir).map_err(|e| format!("mkdir failed: {}", e))?; @@ -2568,17 +2749,17 @@ async fn seed_demo(app: tauri::AppHandle) -> Result { // clips, ~450 KB each, embedded via include_bytes!): // Anna → female reader, ~10s, literary narration. // Marek → male reader, ~9s, calm narration. - // Reference text was produced by Parakeet ASR over the same WAV — close - // enough to verbatim for ICL. + // Reference text must be exact for Qwen3-TTS ICL. A stale Anna transcript + // leaked prompt words into the synthesized take, while Marek stayed clean. let ref_specs: [(&[u8], &str, &str); 2] = [ ( include_bytes!("../resources/voices/anna.wav"), - "The Hispaniola was rolling scuppers under in the ocean swell. The booms were tearing at the blocks, ruddering.", + DEMO_ANNA_REFERENCE_TEXT, "ref-anna.wav", ), ( include_bytes!("../resources/voices/marek.wav"), - "It is a pretty little spot there, a green grass plateau running along by the water's edge and overhung by willows.", + DEMO_MAREK_REFERENCE_TEXT, "ref-marek.wav", ), ]; @@ -2600,9 +2781,7 @@ async fn seed_demo(app: tauri::AppHandle) -> Result { reference_text: (*ref_text).to_string(), }); } - eprintln!( - "[seed_demo] references ready, starting Qwen3-TTS synthesis (first call downloads model)" - ); + eprintln!("[seed_demo] references ready; synthesis is on demand"); // Step 2 — demo lines, each wrapped in a VoxCPM2 style marker. The // sidecar's extractFirstEmotionTag pulls the tag name out and passes it @@ -2623,26 +2802,55 @@ async fn seed_demo(app: tauri::AppHandle) -> Result { // attach its path so the user can immediately play it; otherwise leave // audio_path = None and let the user trigger synthesis explicitly via // Regenerate. No Qwen3 calls happen here — Load demo is ~instant. - let cache_dir = clip_cache_dir(); - let mut clips = Vec::with_capacity(lines.len()); - for (idx, (speaker_idx, text)) in lines.iter().enumerate() { - let stable_id = format!("demo-s{}-l{}-{:x}", speaker_idx, idx, short_hash(text)); - let cached_path = cache_dir.join(format!("{}.wav", stable_id)); - let (audio_path, duration_sec) = if cached_path.exists() { - let dur = wav_duration_sec(&cached_path).ok(); - (Some(cached_path.to_string_lossy().to_string()), dur) - } else { - (None, None) - }; + let clips = demo_clip_seeds("demo", &lines); - clips.push(DemoClipSeed { - speaker_index: *speaker_idx, - audio_path, - duration_sec, - text: (*text).to_string(), + Ok(DemoSeed { voices, clips }) +} + +#[tauri::command] +async fn seed_hindi_demo(app: tauri::AppHandle) -> Result { + eprintln!("[seed_hindi_demo] start"); + emit_progress(&app, "references", 0, 1, "Preparing Hindi reference voice…"); + let dir = std::env::temp_dir().join("soniqo-demo"); + std::fs::create_dir_all(&dir).map_err(|e| format!("mkdir failed: {}", e))?; + + // Two FLEURS hi_in test-split speakers (CC-BY, PCM16 mono 16 kHz), one per + // gender. Reference text must be exact for voice-clone ICL — both + // transcripts are the raw FLEURS transcriptions, ASR-verified against the + // audio (a mismatched transcript leaks prompt words into the takes). + let ref_specs: [(&[u8], &str, &str); 2] = [ + ( + include_bytes!("../resources/voices/hindi_fleurs.wav"), + "लूना को साथी पहलवानों ने भी श्रद्धांजलि दी.", + "ref-hindi-fleurs.wav", + ), + ( + include_bytes!("../resources/voices/hindi_fleurs_female.wav"), + "यह शहर देश के बाकी शहरों से अलग है क्योंकि यह किसी अफ्रीकी शहर की बजाय अरब शहर लगता है.", + "ref-hindi-fleurs-female.wav", + ), + ]; + + let mut voices = Vec::with_capacity(ref_specs.len()); + for (bytes, ref_text, filename) in ref_specs.iter() { + let path = dir.join(filename); + std::fs::write(&path, bytes) + .map_err(|e| format!("write {} failed: {}", path.display(), e))?; + voices.push(DemoVoiceSeed { + reference_audio_path: path.to_string_lossy().to_string(), + reference_text: (*ref_text).to_string(), }); } + // Male (0) and female (1) speakers alternate, like the English demo. + let lines: [(usize, &str); 4] = [ + (0, "(happy) नमस्ते, आज हम हिंदी आवाज़ का परीक्षण कर रहे हैं।"), + (1, "(sad) यह पंक्ति शांत और भावुक सुनाई देनी चाहिए।"), + (0, "(angry) अब आवाज़ में थोड़ी तीव्रता और ज़ोर चाहिए।"), + (1, "(surprised) अंत में यह वाक्य साफ़ और उत्साहित होना चाहिए।"), + ]; + let clips = demo_clip_seeds("demo-hi", &lines); + Ok(DemoSeed { voices, clips }) } @@ -3029,6 +3237,7 @@ pub fn run() { .invoke_handler(tauri::generate_handler![ ping_sidecar, available_tts_engines, + available_asr_models, init_model, interrupt_model_load, pick_video, @@ -3036,6 +3245,8 @@ pub fn run() { import_reference_audio, probe_reference, clone_voice, + save_dictation_audio, + transcribe_audio, synthesize_clip, export_project, list_projects, @@ -3043,6 +3254,7 @@ pub fn run() { load_project, delete_project, seed_demo, + seed_hindi_demo, ]) .run(tauri::generate_context!()) .expect("error while running tauri application"); @@ -3056,10 +3268,16 @@ mod tests { fn tts_engine_protocol_names_are_stable() { let cosy: TtsEngine = serde_json::from_str("\"cosyvoice\"").unwrap(); assert_eq!(cosy, TtsEngine::CosyVoice); + let parakeet: AsrModel = serde_json::from_str("\"parakeet-tdt-v3\"").unwrap(); + assert_eq!(parakeet, AsrModel::ParakeetTdtV3); assert_eq!( serde_json::to_string(&TtsEngine::VoxCPM2).unwrap(), "\"voxcpm2\"" ); + assert_eq!( + serde_json::to_string(&AsrModel::ParakeetTdtV3).unwrap(), + "\"parakeet-tdt-v3\"" + ); assert_eq!( serde_json::to_string(&TtsEngine::IndicMio).unwrap(), "\"indic-mio\"" @@ -3077,6 +3295,7 @@ mod tests { TtsEngine::FishAudio.sidecar_command(), "synthesize_fish_audio" ); + assert_eq!(parakeet.sidecar_command(), "transcribe_parakeet"); } #[test] @@ -3113,6 +3332,15 @@ mod tests { assert!(!TtsEngine::VoxCPM2.requires_reference_transcript()); } + #[test] + fn demo_anna_reference_transcript_matches_bundled_audio() { + assert!( + !DEMO_ANNA_REFERENCE_TEXT.contains("ruddering"), + "stale Anna transcript leaks reference text into Qwen3-TTS ICL output" + ); + assert!(DEMO_ANNA_REFERENCE_TEXT.ends_with("The rudder was banging.")); + } + #[test] fn chatterbox_engine_wiring() { let c: TtsEngine = serde_json::from_str("\"chatterbox\"").unwrap(); @@ -3133,28 +3361,149 @@ mod tests { #[test] fn tts_engine_info_exposes_model_capabilities() { + let vox = tts_engine_info(TtsEngine::VoxCPM2); + assert_eq!(vox.languages.len(), 30); + assert!(vox.languages.iter().any(|language| language == "hi")); + assert!(vox.languages.iter().any(|language| language == "vi")); + assert!(!vox.requires_language); + assert_eq!(vox.model_name, "voxcpm2-mlx-bf16"); + assert_eq!(vox.model_id, "aufklarer/VoxCPM2-MLX-bf16"); + assert_eq!(vox.precision, "bf16"); + + let cosy = tts_engine_info(TtsEngine::CosyVoice); + assert!(cosy.requires_language); + assert_eq!( + cosy.languages, + ["en", "zh", "ja", "ko", "de", "es", "fr", "it", "ru"] + ); + assert!(cosy + .supported_markers + .iter() + .any(|marker| marker == "excited")); + let qwen = tts_engine_info(TtsEngine::Qwen3); assert_eq!(qwen.model_name, "qwen3-tts-1.7b-mlx-bf16"); assert_eq!(qwen.model_id, "aufklarer/Qwen3-TTS-12Hz-1.7B-Base-MLX-bf16"); - assert_eq!(qwen.voice_profile_modes, &["reference-clone"]); + assert_eq!(qwen.voice_profile_modes, ["reference-clone"]); assert!(qwen.requires_reference_audio); assert!(qwen.requires_reference_transcript); + assert!(qwen.requires_language); assert!(!qwen.supports_instruct); assert_eq!(qwen.style_mode, "none"); - assert!(qwen.languages.contains(&"en")); - assert!(qwen.languages.contains(&"ru")); + assert!(qwen.languages.iter().any(|language| language == "en")); + assert!(qwen.languages.iter().any(|language| language == "ru")); assert!(qwen.supported_markers.is_empty()); + assert_eq!(qwen.precision, "bf16"); + + let chatterbox = tts_engine_info(TtsEngine::Chatterbox); + assert_eq!(chatterbox.languages.len(), 22); + assert!(chatterbox.languages.iter().any(|language| language == "zh")); + assert!(chatterbox.languages.iter().any(|language| language == "ja")); + assert!(!chatterbox.languages.iter().any(|language| language == "he")); + assert!(chatterbox.languages.iter().any(|language| language == "ko")); + assert_eq!(chatterbox.precision, "fp16"); + + let omni = tts_engine_info(TtsEngine::OmniVoice); + assert_eq!(omni.model_name, "omnivoice-mlx-fp16"); + assert_eq!(omni.model_id, "aufklarer/OmniVoice-MLX-fp16"); + assert_eq!(omni.precision, "fp16"); let fish = tts_engine_info(TtsEngine::FishAudio); assert_eq!(fish.style_mode, "bracket-tag"); - assert!(fish.supported_markers.contains(&"excited")); + assert!(fish.languages.len() > 70); + assert!(fish + .benchmark_languages + .iter() + .any(|language| language == "hi")); + assert!(fish + .supported_markers + .iter() + .any(|marker| marker == "excited")); assert_eq!(fish.use_policy, "research-only"); assert!(!fish.needs_trim); } + #[test] + fn hindi_demo_reference_is_bundled_pcm_wav() { + let path = std::env::temp_dir().join(format!( + "speech-studio-hindi-ref-{}.wav", + uuid::Uuid::new_v4().simple() + )); + std::fs::write( + &path, + include_bytes!("../resources/voices/hindi_fleurs.wav"), + ) + .unwrap(); + + let (sample_rate, channels, bits) = read_wav_header(&path).unwrap(); + assert_eq!(sample_rate, 16_000); + assert_eq!(channels, 1); + assert_eq!(bits, 16); + + let duration = wav_duration_sec(&path).unwrap(); + assert!( + (3.7..4.0).contains(&duration), + "unexpected Hindi reference duration: {duration}" + ); + + let _ = std::fs::remove_file(path); + } + + #[test] + fn tts_registry_defaults_keep_16bit_precision_floor() { + for entry in MODEL_REGISTRY + .tts_engines + .iter() + .filter(|entry| engine_is_supported(entry.info.id)) + { + assert!( + matches!(entry.info.precision.as_str(), "bf16" | "fp16"), + "{} default precision should stay 16-bit, got {}", + entry.info.model_name, + entry.info.precision + ); + assert!( + !entry.info.model_id.contains("int8") + && !entry.info.model_id.contains("8bit") + && !entry.info.model_id.contains("4bit"), + "{} default model id should not be quantized: {}", + entry.info.model_name, + entry.info.model_id + ); + } + } + + #[test] + fn asr_registry_uses_parakeet_family_on_all_platforms() { + let parakeet = asr_model_info(AsrModel::ParakeetTdtV3); + assert_eq!(parakeet.model_name, "parakeet-tdt-v3-0.6b-int8"); + assert_eq!(parakeet.sample_rate, 16_000); + assert_eq!(parakeet.max_segment_sec, 30); + assert!(parakeet.streaming); + assert_eq!(parakeet.readiness, "production"); + assert_eq!(parakeet.languages, ["en"]); + assert_eq!( + parakeet.runtime, + if cfg!(target_os = "macos") { + "coreml" + } else { + "litert" + } + ); + assert_eq!( + parakeet.model_id, + if cfg!(target_os = "macos") { + "aufklarer/Parakeet-TDT-v3-CoreML-INT8-30s" + } else { + "soniqo/Parakeet-TDT-0.6B-v3-LiteRT-INT8" + } + ); + } + #[test] fn studio_registry_keeps_qwen_on_bf16() { - let ids: Vec = TTS_ENGINE_REGISTRY + let ids: Vec = MODEL_REGISTRY + .tts_engines .iter() .map(|entry| entry.info.id) .collect(); @@ -3180,11 +3529,29 @@ mod tests { assert!(!qwen.info.model_name.contains("8bit")); assert!(!qwen.info.model_id.contains("8bit")); assert!(!qwen.info.model_name.contains("0.6b")); + assert_eq!(qwen.info.precision, "bf16"); assert_eq!(qwen.info.style_mode, "none"); } + #[test] + fn qwen_synth_budget_is_bounded_for_short_lines() { + assert_eq!(synth_seed_ladder(TtsEngine::CosyVoice).len(), 6); + assert_eq!(synth_max_tokens(TtsEngine::Qwen3, 2), 40); + assert_eq!(synth_max_tokens(TtsEngine::Qwen3, 6), 44); + assert_eq!(synth_max_tokens(TtsEngine::Qwen3, 20), 96); + assert_eq!(synth_max_tokens(TtsEngine::CosyVoice, 6), 112); + } + #[test] fn sidecar_language_normalization_preserves_chatterbox_hi() { + assert_eq!( + normalize_sidecar_language(TtsEngine::CosyVoice, Some("ru")).as_deref(), + Some("russian") + ); + assert_eq!( + normalize_sidecar_language(TtsEngine::CosyVoice, Some("ja")).as_deref(), + Some("japanese") + ); assert_eq!( normalize_sidecar_language(TtsEngine::Chatterbox, Some("hi")).as_deref(), Some("hi") @@ -3247,6 +3614,21 @@ mod tests { ); } + #[test] + fn dictation_cache_dir_under_app_namespace() { + let dir = dictation_cache_dir(); + assert!( + dir.ends_with("dictation"), + "dictation dir should end with dictation: {:?}", + dir + ); + assert!( + dir.to_string_lossy().contains("audio.soniqo.studio"), + "dictation dir should be under the app namespace: {:?}", + dir + ); + } + // Simulates the installed-bundle layout: the sidecar binary sits next to // the main app binary while libLiteRt is staged in a separate resource dir. // The search path must include both so the loader finds the runtime. diff --git a/src-tauri/tests/sidecar.rs b/src-tauri/tests/sidecar.rs index bf11660..41f7622 100644 --- a/src-tauri/tests/sidecar.rs +++ b/src-tauri/tests/sidecar.rs @@ -680,7 +680,7 @@ fn bundled_voice_path(name: &str) -> PathBuf { } // Reference text for the bundled WAVs. Must match seed_demo in src/lib.rs. -const ANNA_REF_TEXT: &str = "The Hispaniola was rolling scuppers under in the ocean swell. The booms were tearing at the blocks, ruddering."; +const ANNA_REF_TEXT: &str = "The Hispaniola was rolling scuppers under in the ocean swell. The booms were tearing at the blocks. The rudder was banging."; const MAREK_REF_TEXT: &str = "It is a pretty little spot there, a green grass plateau running along by the water's edge and overhung by willows."; // Demo target lines. Must match `lines` in `seed_demo`. @@ -933,3 +933,273 @@ fn demo_references_e2e() { overall * 100.0 ); } + +// ----------------------------------------------------------------------------- +// Onset-junk + emotion-marker e2e tests. +// +// Qwen3 ICL and OmniVoice both opened some renders (reference-dependent) with +// a short low-level codec artifact before the first word — quiet hiss for +// Qwen3 on the Marek reference, a low hum for OmniVoice on Anna — followed by +// a silence gap before the phrase. The sidecar removes these via +// trimLeadingJunk before edge conditioning. These tests replay the exact +// production requests that used to produce audible junk (deterministic at +// seed 1000) and assert the first thing you hear is speech-loud. +// +// Indic-Mio styles via a closed suffix-tag vocabulary; the sidecar maps the +// Studio's inline "(happy)"-style marker onto it. Before that mapping the +// model read the marker aloud, so the third test pins "marker is styled, not +// spoken". +// +// All three load real models (cached under ~/.cache/huggingface after the +// first run) and need the `speech` CLI for Parakeet grading. Opt in via: +// cargo test --test sidecar -- --ignored --nocapture qwen_onset_is_speech_not_junk +// cargo test --test sidecar -- --ignored --nocapture omnivoice_onset_is_speech_not_junk +// cargo test --test sidecar -- --ignored --nocapture indic_mio_does_not_speak_emotion_marker +// ----------------------------------------------------------------------------- + +/// Read a sidecar-written WAV (44-byte header, 16-bit PCM mono) as f32 samples. +fn read_wav_samples(path: &str) -> (Vec, usize) { + use std::io::Read; + let mut f = std::fs::File::open(path).expect("open wav"); + let mut header = [0u8; 44]; + f.read_exact(&mut header).expect("wav header"); + let channels = u16::from_le_bytes([header[22], header[23]]) as usize; + let sample_rate = u32::from_le_bytes([header[24], header[25], header[26], header[27]]) as usize; + let bps = u16::from_le_bytes([header[34], header[35]]); + assert_eq!(bps, 16, "expected 16-bit PCM"); + assert_eq!(channels, 1, "expected mono"); + let mut buf = Vec::new(); + f.read_to_end(&mut buf).expect("wav data"); + let samples = buf + .chunks_exact(2) + .map(|c| i16::from_le_bytes([c[0], c[1]]) as f32 / 32768.0) + .collect(); + (samples, sample_rate) +} + +/// Group audio into energy islands (5 ms RMS windows above -60 dBFS, closed +/// by ≥50 ms of quiet) and return (first_island_peak_db, max_island_peak_db). +/// Mirrors the sidecar's trimLeadingJunk analysis: a clean render opens with +/// a speech-loud island; onset junk shows up as a first island far below the +/// loudest one (measured 10-28 dB down across both engines). +fn onset_island_peaks(samples: &[f32], sample_rate: usize) -> Option<(f64, f64)> { + let win = sample_rate * 5 / 1000; + if win == 0 || samples.len() < win * 8 { + return None; + } + let dbs: Vec = samples + .chunks_exact(win) + .map(|c| { + let e = c.iter().map(|s| (*s as f64) * (*s as f64)).sum::() / c.len() as f64; + if e > 0.0 { 10.0 * e.log10() } else { -120.0 } + }) + .collect(); + let mut peaks: Vec = Vec::new(); + let mut current: Option = None; + let mut quiet = 0; + for &db in &dbs { + if db > -60.0 { + current = Some(current.map_or(db, |p: f64| p.max(db))); + quiet = 0; + } else if let Some(peak) = current { + quiet += 1; + if quiet >= 10 { + peaks.push(peak); + current = None; + } + } + } + if let Some(peak) = current { + peaks.push(peak); + } + let first = *peaks.first()?; + let max = peaks.iter().cloned().fold(f64::MIN, f64::max); + Some((first, max)) +} + +fn parakeet_transcript(audio_path: &str) -> String { + let out = Command::new("speech") + .args(["transcribe", audio_path, "--engine", "parakeet"]) + .output() + .expect("run `speech transcribe` (install the speech CLI for e2e tests)"); + assert!( + out.status.success(), + "speech transcribe failed: {}", + String::from_utf8_lossy(&out.stderr) + ); + String::from_utf8_lossy(&out.stdout) + .lines() + .find_map(|l| l.strip_prefix("Result: ")) + .map(|s| s.trim().to_string()) + .unwrap_or_default() +} + +/// Send one synthesis request, assert success, and return the output path. +fn synth_expect_ok(s: &mut SidecarHandle, payload: serde_json::Value) -> String { + let id = payload["id"].as_str().unwrap_or("").to_string(); + s.send(&payload); + let v = s.recv(); + assert_eq!(v["id"], serde_json::Value::String(id)); + assert_eq!( + v["ok"], + true, + "synthesis failed: {}", + v["error"].as_str().unwrap_or("(no error)") + ); + let path = v["result"]["audioPath"].as_str().expect("audioPath").to_string(); + let dur = v["result"]["durationSec"].as_f64().unwrap_or(0.0); + assert!( + (1.0..=15.0).contains(&dur), + "implausible duration {:.2}s for {}", + dur, + path + ); + path +} + +/// The first energy island must be speech, not a quiet junk prefix. 8 dB is +/// the sidecar detector's own quiet-junk bound: clean takes measured ≤4.7 dB +/// below the loudest island, junk takes ≥10.2 dB. +fn assert_onset_is_speech(audio_path: &str, target_text: &str) { + let (samples, sample_rate) = read_wav_samples(audio_path); + let (first_peak, max_peak) = + onset_island_peaks(&samples, sample_rate).expect("no energy islands in output"); + let deficit = max_peak - first_peak; + assert!( + deficit <= 8.0, + "onset junk: first island peaks {:.1} dB below the loudest ({:.1} vs {:.1} dBFS) in {}", + deficit, + first_peak, + max_peak, + audio_path + ); + let transcript = parakeet_transcript(audio_path); + let (_, _, cov) = token_coverage(target_text, &transcript); + assert!( + cov >= 0.6, + "coverage {:.0}% < 60% — transcript {:?} vs target {:?}", + cov * 100.0, + transcript, + target_text + ); +} + +#[test] +#[ignore] +fn qwen_onset_is_speech_not_junk() { + let marek = bundled_voice_path("marek"); + let mut s = SidecarHandle::spawn(); + // The exact production request (post-preprocess text, seed 1000) that + // used to open with ~100 ms of quiet hiss followed by half a second of + // silence before the phrase. + let path = synth_expect_ok( + &mut s, + serde_json::json!({ + "id": "e2e-qwen-onset", + "command": "synthesize_icl", + "engine": "qwen3", + "text": "Then we end this together, Tonight.", + "voiceId": "marek", + "referenceAudioPath": marek.to_string_lossy(), + "referenceText": MAREK_REF_TEXT, + "seed": 1000, + "maxTokens": 44, + }), + ); + assert_onset_is_speech(&path, "Then we end this together, Tonight."); +} + +#[test] +#[ignore] +fn omnivoice_onset_is_speech_not_junk() { + let anna = bundled_voice_path("anna"); + let mut s = SidecarHandle::spawn(); + // OmniVoice's variant of the same artifact: a ~200 ms low hum on the + // Anna reference before the first word. + let path = synth_expect_ok( + &mut s, + serde_json::json!({ + "id": "e2e-omni-onset", + "command": "synthesize_omnivoice", + "engine": "omnivoice", + "modelId": "aufklarer/OmniVoice-MLX-fp16", + "text": "(dramatic) I never thought we'd make it this far.", + "voiceId": "anna", + "referenceAudioPath": anna.to_string_lossy(), + "referenceText": ANNA_REF_TEXT, + "language": "en", + "seed": 1000, + }), + ); + assert_onset_is_speech(&path, "I never thought we'd make it this far."); +} + +#[test] +#[ignore] +fn indic_mio_does_not_speak_emotion_marker() { + let anna = bundled_voice_path("anna"); + let mut s = SidecarHandle::spawn(); + let target = "This line should sound bright and clear."; + let path = synth_expect_ok( + &mut s, + serde_json::json!({ + "id": "e2e-indic-marker", + "command": "synthesize_indic_mio", + "engine": "indic-mio", + "modelId": "aufklarer/Indic-Mio-MLX-fp16", + "text": format!("(happy) {}", target), + "voiceId": "indic-test", + "referenceAudioPath": anna.to_string_lossy(), + "referenceText": ANNA_REF_TEXT, + "language": "en", + "seed": 1000, + }), + ); + let transcript = parakeet_transcript(&path); + let (_, _, cov) = token_coverage(target, &transcript); + assert!( + cov >= 0.6, + "coverage {:.0}% < 60% — transcript {:?}", + cov * 100.0, + transcript + ); + assert!( + !tokenize(&transcript).contains(&"happy".to_string()), + "emotion marker was spoken aloud — transcript {:?}", + transcript + ); +} + +#[test] +fn sidecar_rejects_engine_mismatch() { + let mut s = SidecarHandle::spawn(); + s.send(&serde_json::json!({ + "id": "mismatch", + "command": "synthesize_omnivoice", + "engine": "qwen3", + "text": "hi", + "referenceAudioPath": "/nonexistent.wav", + })); + let v = s.recv(); + assert_eq!(v["ok"], false); + let err = v["error"].as_str().unwrap_or(""); + assert!( + err.contains("requires engine"), + "unexpected error: {}", + err + ); +} + +#[test] +fn sidecar_rejects_indic_mio_without_text() { + let mut s = SidecarHandle::spawn(); + s.send(&serde_json::json!({ + "id": "no-text", + "command": "synthesize_indic_mio", + "engine": "indic-mio", + })); + let v = s.recv(); + assert_eq!(v["ok"], false); + let err = v["error"].as_str().unwrap_or(""); + assert!(err.contains("requires text"), "unexpected error: {}", err); +} diff --git a/src/components/DictationPanel.tsx b/src/components/DictationPanel.tsx new file mode 100644 index 0000000..b2fab45 --- /dev/null +++ b/src/components/DictationPanel.tsx @@ -0,0 +1,408 @@ +import { useEffect, useRef, useState } from "react"; +import { Clipboard, FilePlus2, Loader2, Mic, Pause, Play, Square } from "lucide-react"; +import { convertFileSrc } from "@tauri-apps/api/core"; +import { + availableAsrModels, + saveDictationAudio, + transcribeAudio, + type AsrModelInfo, + type TranscribeAudioResult, +} from "../ipc/commands"; +import { newClip, useProjectStore } from "../state/projectStore"; +import type { SpeakerTrack } from "../types/project"; +import { Button } from "./ui/button"; +import { useI18n } from "../i18n/useI18n"; + +interface RecorderSession { + stream: MediaStream; + context: AudioContext; + source: MediaStreamAudioSourceNode; + processor: ScriptProcessorNode; + chunks: Float32Array[]; + sampleRate: number; + startedAt: number; +} + +interface DictationCapture { + id: string; + audioPath: string; + durationSec: number; + text: string; + elapsedSec: number; + createdAt: string; +} + +let currentDictationAudio: HTMLAudioElement | null = null; + +function flattenChunks(chunks: Float32Array[]): Float32Array { + const total = chunks.reduce((sum, chunk) => sum + chunk.length, 0); + const out = new Float32Array(total); + let offset = 0; + for (const chunk of chunks) { + out.set(chunk, offset); + offset += chunk.length; + } + return out; +} + +function writeAscii(view: DataView, offset: number, value: string) { + for (let i = 0; i < value.length; i += 1) { + view.setUint8(offset + i, value.charCodeAt(i)); + } +} + +function encodeWav(samples: Float32Array, sampleRate: number): ArrayBuffer { + const bytesPerSample = 2; + const dataBytes = samples.length * bytesPerSample; + const buffer = new ArrayBuffer(44 + dataBytes); + const view = new DataView(buffer); + writeAscii(view, 0, "RIFF"); + view.setUint32(4, 36 + dataBytes, true); + writeAscii(view, 8, "WAVE"); + writeAscii(view, 12, "fmt "); + view.setUint32(16, 16, true); + view.setUint16(20, 1, true); + view.setUint16(22, 1, true); + view.setUint32(24, sampleRate, true); + view.setUint32(28, sampleRate * bytesPerSample, true); + view.setUint16(32, bytesPerSample, true); + view.setUint16(34, 16, true); + writeAscii(view, 36, "data"); + view.setUint32(40, dataBytes, true); + let offset = 44; + for (const sample of samples) { + const clamped = Math.max(-1, Math.min(1, sample)); + view.setInt16(offset, Math.round(clamped * 32767), true); + offset += bytesPerSample; + } + return buffer; +} + +function arrayBufferToBase64(buffer: ArrayBuffer): string { + const bytes = new Uint8Array(buffer); + const chunkSize = 0x8000; + let binary = ""; + for (let i = 0; i < bytes.length; i += chunkSize) { + binary += String.fromCharCode(...bytes.subarray(i, i + chunkSize)); + } + return btoa(binary); +} + +function formatSec(value: number): string { + return value.toFixed(value < 10 ? 1 : 0); +} + +function estimateClipDurationSec(text: string, fallbackSec: number): number { + const words = text.trim().split(/\s+/).filter(Boolean).length; + return Math.max(1.0, fallbackSec || words * 0.35 || 1.0); +} + +export function DictationPanel() { + const { messages: t } = useI18n(); + const addTrack = useProjectStore((s) => s.addTrack); + const addClip = useProjectStore((s) => s.addClip); + const updateClip = useProjectStore((s) => s.updateClip); + const select = useProjectStore((s) => s.select); + const [models, setModels] = useState([]); + const [recording, setRecording] = useState(false); + const [busy, setBusy] = useState(false); + const [error, setError] = useState(null); + const [flowMessage, setFlowMessage] = useState(null); + const [captures, setCaptures] = useState([]); + const [playingId, setPlayingId] = useState(null); + const recorderRef = useRef(null); + + const model = models[0]; + + useEffect(() => { + let cancelled = false; + void availableAsrModels() + .then((next) => { + if (!cancelled) setModels(next); + }) + .catch((e) => { + if (!cancelled) setError(String(e)); + }); + return () => { + cancelled = true; + stopRecorderOnly(); + if (currentDictationAudio) { + currentDictationAudio.pause(); + currentDictationAudio = null; + } + }; + }, []); + + function stopRecorderOnly(): RecorderSession | null { + const session = recorderRef.current; + recorderRef.current = null; + if (!session) return null; + session.processor.disconnect(); + session.source.disconnect(); + session.stream.getTracks().forEach((track) => track.stop()); + void session.context.close(); + setRecording(false); + return session; + } + + async function startRecording() { + setError(null); + setFlowMessage(null); + if (!navigator.mediaDevices?.getUserMedia) { + setError(t.dictation.unsupported); + return; + } + try { + const stream = await navigator.mediaDevices.getUserMedia({ + audio: { + echoCancellation: true, + noiseSuppression: true, + autoGainControl: true, + channelCount: 1, + }, + }); + const AudioContextCtor = window.AudioContext; + const context = new AudioContextCtor({ sampleRate: 16000 }); + const source = context.createMediaStreamSource(stream); + const processor = context.createScriptProcessor(4096, 1, 1); + const chunks: Float32Array[] = []; + processor.onaudioprocess = (event) => { + chunks.push(new Float32Array(event.inputBuffer.getChannelData(0))); + event.outputBuffer.getChannelData(0).fill(0); + }; + source.connect(processor); + processor.connect(context.destination); + recorderRef.current = { + stream, + context, + source, + processor, + chunks, + sampleRate: context.sampleRate, + startedAt: performance.now(), + }; + setRecording(true); + } catch (e) { + setError(t.dictation.micFailed(String(e))); + } + } + + async function stopAndTranscribe() { + const session = stopRecorderOnly(); + if (!session || busy) return; + const samples = flattenChunks(session.chunks); + const durationSec = samples.length / session.sampleRate; + if (durationSec < 0.2) { + setError(t.dictation.tooShort); + return; + } + + setBusy(true); + setError(null); + setFlowMessage(null); + try { + const wav = encodeWav(samples, session.sampleRate); + const saved = await saveDictationAudio(arrayBufferToBase64(wav)); + const transcript: TranscribeAudioResult = await transcribeAudio({ + audioPath: saved.audioPath, + model: model?.id, + }); + setCaptures((prev) => [ + { + id: crypto.randomUUID(), + audioPath: saved.audioPath, + durationSec: transcript.durationSec || saved.durationSec || durationSec, + text: transcript.text, + elapsedSec: transcript.elapsedSec, + createdAt: new Date().toISOString(), + }, + ...prev, + ]); + } catch (e) { + setError(t.dictation.transcribeFailed(String(e))); + } finally { + setBusy(false); + } + } + + function insertCapture(capture: DictationCapture) { + const text = capture.text.trim(); + if (!text) { + setError(t.dictation.emptyTranscript); + return; + } + const state = useProjectStore.getState(); + if (state.selection.kind === "clip") { + updateClip(state.selection.id, { + text, + renderedAudioPath: undefined, + locked: false, + }); + setFlowMessage(t.dictation.insertedClip); + return; + } + + const selectedTrackId = state.selection.kind === "track" ? state.selection.id : undefined; + const selectedTrack = selectedTrackId + ? state.project.tracks.find( + (track): track is SpeakerTrack => + track.kind === "speaker" && track.id === selectedTrackId, + ) + : undefined; + let targetTrack = selectedTrack ?? state.project.tracks.find( + (track): track is SpeakerTrack => track.kind === "speaker", + ); + if (!targetTrack) { + targetTrack = { + kind: "speaker", + id: crypto.randomUUID(), + name: t.defaults.speakerTrack(1), + clips: [], + }; + addTrack(targetTrack); + } + + const startSec = Math.max(0, state.transport.positionSec); + const endSec = startSec + estimateClipDurationSec(text, capture.durationSec); + const clip = newClip({ + trackId: targetTrack.id, + startSec, + endSec, + text, + }); + addClip(clip); + select({ kind: "clip", id: clip.id }); + setFlowMessage(t.dictation.insertedTimeline); + } + + function togglePlayback(capture: DictationCapture) { + if (playingId === capture.id) { + currentDictationAudio?.pause(); + currentDictationAudio = null; + setPlayingId(null); + return; + } + currentDictationAudio?.pause(); + const audio = new Audio(convertFileSrc(capture.audioPath)); + currentDictationAudio = audio; + audio.onended = () => { + if (currentDictationAudio === audio) currentDictationAudio = null; + setPlayingId(null); + }; + audio.onerror = () => setPlayingId(null); + audio.play().then(() => setPlayingId(capture.id)).catch(() => setPlayingId(null)); + } + + return ( +

+
+ + {t.dictation.title} + + + {model ? model.displayName : t.dictation.loadingModel} + +
+ +
+ +
+ {model ? t.dictation.modelMeta(model.runtime, model.modelSize) : t.dictation.modelPending} +
+
+ + {error && ( +
+ {error} +
+ )} + {flowMessage && ( +
+ {flowMessage} +
+ )} + +
+ {captures.length === 0 && ( +
+ {t.dictation.empty} +
+ )} + {captures.map((capture) => ( +
+
+ + {t.dictation.captureMeta( + formatSec(capture.durationSec), + formatSec(capture.elapsedSec), + )} + +
+ + + +
+
+

+ {capture.text || t.dictation.emptyTranscript} +

+
+ ))} +
+
+ ); +} diff --git a/src/components/Inspector.tsx b/src/components/Inspector.tsx index 6413a21..87d66ba 100644 --- a/src/components/Inspector.tsx +++ b/src/components/Inspector.tsx @@ -1,5 +1,4 @@ import { useState } from "react"; -import { convertFileSrc } from "@tauri-apps/api/core"; import { Lock, Unlock, Trash2, RefreshCw, History, Loader2 } from "lucide-react"; import { useProjectStore } from "../state/projectStore"; import { ScriptEditor } from "./ScriptEditor"; @@ -15,6 +14,8 @@ import { SelectValue, } from "./ui/select"; import { cn } from "@/lib/utils"; +import { clipAudioVersion } from "../lib/clipAudio"; +import { mediaFileSrc } from "../lib/mediaSrc"; import { dateLocale, type Messages } from "../i18n/messages"; import { useI18n } from "../i18n/useI18n"; @@ -62,8 +63,10 @@ export function Inspector() { const updateClip = useProjectStore((s) => s.updateClip); const assignVoiceToTrack = useProjectStore((s) => s.assignVoiceToTrack); const removeClip = useProjectStore((s) => s.removeClip); + const setPlaying = useProjectStore((s) => s.setPlaying); + const seek = useProjectStore((s) => s.seek); const engine = useProjectStore((s) => s.model.engine); - const language = useProjectStore((s) => s.model.language); + const modelLanguage = useProjectStore((s) => s.model.language); const activeEngine = useProjectStore((s) => s.model.engines.find((candidate) => candidate.id === s.model.engine), ); @@ -257,6 +260,7 @@ export function Inspector() { const needsReferenceTranscript = activeEngine?.requiresReferenceTranscript ?? (engine === "cosyvoice" || engine === "qwen3" || engine === "fish-audio"); + const language = activeEngine?.requiresLanguage ? modelLanguage : undefined; const transcriptEngineName = activeEngine?.displayName ?? t.inspector.selectedEngine; const canRegenerate = !isRegenerating && @@ -267,6 +271,8 @@ export function Inspector() { async function regenerate() { if (!effectiveVoice || !effectiveVoice.referenceAudioPath) return; + setPlaying(false); + seek(current.startSec); setIsRegenerating(true); setRegenError(null); setRegenTiming(null); @@ -391,8 +397,8 @@ export function Inspector() {