This repository contains procedure for training and inferring your own wav2vec 2.0 model. We also provide pre-trained wav2vec 2.0 weights for 7 Indian languages. Work was done for INTERSPEECH 2021 special challenge "Multilingual and code-switching ASR challenges for low resource Indian languages".
Link to wav2vec 2.0 pre-trained weights
To know how to run inference on your own files, please refer to the run_inference folder. To train your own weights please refer to the run_train folder.
| Language | Mean | Max | Min | Total Files |
|---|---|---|---|---|
| 7 Indian Languages | 5.80 | 60.0 | 0.0 | 479127 |
| Language | Mean | Max | Min | Total Files |
|---|---|---|---|---|
| 7 Indian Languages | 5.81 | 60.0 | 0.0 | 25036 |
| Language | Mean | Max | Min | Total Files |
|---|---|---|---|---|
| Hindi | 3.42 | 15.9 | 1.02 | 99925 |
| Odia | 5.69 | 48.11 | 1.51 | 59782 |
| Marathi | 4.26 | 52.52 | 1.0 | 79432 |
| Gujarati | 6.31 | 23.22 | 1.01 | 22807 |
| Tamil | 3.68 | 18.57 | 0.325 | 39131 |
| Telegu | 3.21 | 23.61 | 0.325 | 44882 |
| Language | Mean | Max | Min | Total Files |
|---|---|---|---|---|
| Hindi | 5.20 | 12.66 | 1.92 | 3843 |
| Odia | 5.7 | 18.41 | 1.56 | 3471 |
| Marathi | 3.85 | 11.48 | 1.0 | 4675 |
| Gujarati | 5.85 | 13.89 | 1.97 | 3075 |
| Tamil | 5.85 | 14.5 | 1.71 | 3081 |
| Telegu | 5.92 | 19.66 | 1.514 | 3040 |
| Language | Mean | Max | Min | Total Files |
|---|---|---|---|---|
| Hindi | 2.97 | 57.0 | 0.2 | 414698 |
| Language | Mean | Max | Min | Total Files |
|---|---|---|---|---|
| Hindi | 2.39 | 41.0 | 0.2 | 33907 |
| Language | Mean | Max | Min | Total Files |
|---|---|---|---|---|
| Bengali | 6.21 | 57.0 | 1.0 | 26606 |
| Language | Mean | Max | Min | Total Files |
|---|---|---|---|---|
| Bengali | 5.90 | 29.0 | 1.0 | 4275 |