📝 Real-Time Transcription App

Powered by Whisper.cpp
Swift | SwiftUI

Description

Effortlessly transcribe audio to text in real time with on-device processing using Whisper.cpp. This app offers multiple preloaded models, performance insights, and a modern SwiftUI design for the ultimate transcription experience.

🚀 Features

• Real-Time Transcription: Accurate, on-device speech-to-text transcription powered by Whisper.cpp.
• Multiple Preloaded Models: Choose from various Whisper models based on your device’s capabilities and transcription requirements.
• Performance Metrics:
  • Memory usage statistics.
  • Processing time for each transcription chunk.
  • Visual tracking of the number of processed chunks.
• SwiftUI Design: A modern, clean, and intuitive user interface.
• Privacy Focused: All processing happens on-device, ensuring user data remains secure.

📸 Screenshots

(Add screenshots or GIFs showcasing the app UI and features.)

---

🛠️ Installation

Prerequisites

• iOS 15+
• Xcode 14+

Steps

1. Clone the repository:

   git clone https://github.com/DeepBhupatkar/swift-whisper.cpp-transcription.git
   cd RealTimeTranscriptionExample  

2. Build and run the app on a physical device or simulator.

---

⚙️ How It Works

1. Model Selection:

• Select a preloaded Whisper model from the settings menu.

• Supported models include tiny, base, small, medium, and large.

• You can download models from below given link and after downloading, place them inside RealTimeTranscription/Resource/models.

  Available Models :

  tiny - Download (F16, 75 MiB)
  tiny-q5_1 - Download (31 MiB)
  tiny-q8_0 - Download (42 MiB)
  tiny.en - Download (F16, 75 MiB)
  tiny.en-q5_1 - Download (31 MiB)
  tiny.en-q8_0 - Download (42 MiB)
  base-q5_1 - Download (57 MiB)
  base-q8_0 - Download (78 MiB)
  base.en-q5_1 - Download (57 MiB)
  base.en-q8_0 - Download (78 MiB)

2. Transcription:

   • Tap the record button to start transcribing in real time.
   • The app processes audio in chunks for seamless transcription.

3. Device Stats:

   • Displays real-time memory usage and chunk processing time to help optimize performance.

---

📊 Performance Metrics

Metric	Description	Example Value
Memory Usage	Tracks how much memory is utilized by the app during transcription.	~200 MB
Processing Time	Measures the time (ms) taken to process each audio chunk.	~50 ms/chunk
Chunks Processed	Tracks how many audio chunks are processed during a transcription session.	120 chunks

---

🧰 Tools and Technologies

• Whisper.cpp: A lightweight Whisper implementation for fast on-device transcription.
• Swift & SwiftUI: For building a modern and efficient iOS application.

---

🤝 Contributing

Contributions are welcome!

1. Fork the repository.
2. Create a feature branch: git checkout -b feature-name.
3. Commit your changes: git commit -m 'Add feature'.
4. Push to the branch: git push origin feature-name.
5. Submit a pull request.

---

📄 License

This project is licensed under the MIT License. See the LICENSE file for details.

---

🙌 Acknowledgments

• Whisper.cpp: For enabling lightweight, efficient on-device transcription.
• OpenAI Whisper: The foundation for Whisper.cpp’s functionality.
• Special thanks to the open-source community for contributing to AI advancements.