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--- |
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license: cc-by-nc-4.0 |
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language: |
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- ru |
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library_name: nemo |
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tags: |
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- tts |
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- text-to-speech |
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- Vocoder |
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--- |
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### How to use |
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See example of inference pipeline for Russian TTS (G2P + FastPitch + HifiGAN) in this [notebook](https://github.com/bene-ges/nemo_compatible/blob/main/notebooks/Russian_TTS_with_IPA_G2P_FastPitch_and_HifiGAN.ipynb). |
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Or use this [bash-script](https://github.com/bene-ges/nemo_compatible/blob/main/scripts/tts/ru_ipa_fastpitch_hifigan/test.sh). |
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### Input |
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This model accepts batches of mel spectrograms. |
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### Output |
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This model outputs audio at 22050Hz. |
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## Training |
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The NeMo toolkit [1] was used for training the model for several epochs. |
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Full training script is [here](https://github.com/bene-ges/nemo_compatible/blob/main/scripts/tts/ru_ipa_fastpitch_hifigan/train.sh). |
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### Datasets |
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This model is trained on [RUSLAN](https://ruslan-corpus.github.io/) [2] corpus (single speaker, male voice) sampled at 22050Hz. |
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## References |
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- [1] [NVIDIA NeMo Toolkit](https://github.com/NVIDIA/NeMo) |
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- [2] Gabdrakhmanov L., Garaev R., Razinkov E. (2019) RUSLAN: Russian Spoken Language Corpus for Speech Synthesis. In: Salah A., Karpov A., Potapova R. (eds) Speech and Computer. SPECOM 2019. Lecture Notes in Computer Science, vol 11658. Springer, Cham |
