by sil-ai
Open source · 212 downloads · 0 likes
This model is a refined version of *microsoft/speecht5_tts*, specifically trained for text-to-speech synthesis. It converts text into natural and expressive speech, with vocal quality optimized for various applications. Its primary use cases include generating voiceovers, providing voice assistance for visually impaired individuals, or creating automated audio content. What sets it apart is its ability to produce more natural intonation and prosody through targeted training, while maintaining the robustness of the base SpeechT5 model.
This model is a fine-tuned version of microsoft/speecht5_tts on the None dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.0864 | 6.4959 | 1000 | 0.0616 |
| 0.0723 | 12.9918 | 2000 | 0.0563 |
| 0.0655 | 19.4829 | 3000 | 0.0578 |
| 0.066 | 25.9788 | 4000 | 0.0527 |
| 0.0606 | 32.4698 | 5000 | 0.0539 |
| 0.0578 | 38.9657 | 6000 | 0.0519 |
| 0.0566 | 45.4568 | 7000 | 0.0531 |
| 0.0579 | 51.9527 | 8000 | 0.0534 |
| 0.0519 | 58.4437 | 9000 | 0.0521 |
| 0.0514 | 64.9396 | 10000 | 0.0544 |
| 0.0497 | 71.4307 | 11000 | 0.0578 |
| 0.0484 | 77.9266 | 12000 | 0.0524 |
| 0.0474 | 84.4176 | 13000 | 0.0526 |
| 0.0457 | 90.9135 | 14000 | 0.0517 |
| 0.0461 | 97.4046 | 15000 | 0.0523 |
| 0.0456 | 103.9005 | 16000 | 0.0530 |
| 0.0436 | 110.3915 | 17000 | 0.0517 |
| 0.042 | 116.8874 | 18000 | 0.0515 |
| 0.0411 | 123.3785 | 19000 | 0.0520 |
| 0.043 | 129.8744 | 20000 | 0.0514 |
| 0.0384 | 136.3654 | 21000 | 0.0529 |
| 0.0383 | 142.8613 | 22000 | 0.0516 |
| 0.0383 | 149.3524 | 23000 | 0.0518 |
| 0.0395 | 155.8483 | 24000 | 0.0520 |
| 0.038 | 162.3393 | 25000 | 0.0522 |
| 0.0383 | 168.8352 | 26000 | 0.0520 |
| 0.0363 | 175.3263 | 27000 | 0.0520 |
| 0.0378 | 181.8222 | 28000 | 0.0529 |
| 0.0373 | 188.3132 | 29000 | 0.0517 |
| 0.0364 | 194.8091 | 30000 | 0.0515 |
| 0.0362 | 201.3002 | 31000 | 0.0522 |
| 0.0365 | 207.7961 | 32000 | 0.0520 |
| 0.0339 | 214.2871 | 33000 | 0.0520 |
| 0.035 | 220.7830 | 34000 | 0.0514 |
| 0.0358 | 227.2741 | 35000 | 0.0522 |
| 0.0333 | 233.7700 | 36000 | 0.0525 |
| 0.0348 | 240.2610 | 37000 | 0.0524 |
| 0.0372 | 246.7569 | 38000 | 0.0519 |
| 0.0349 | 253.2480 | 39000 | 0.0521 |
| 0.0372 | 259.7439 | 40000 | 0.0521 |