--- license: cc-by-nc-4.0 language: - ru library_name: nemo tags: - tts - text-to-speech - Vocoder --- ### How to use 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). Or use this [bash-script](https://github.com/bene-ges/nemo_compatible/blob/main/scripts/tts/ru_ipa_fastpitch_hifigan/test.sh). ### Input This model accepts batches of mel spectrograms. ### Output This model outputs audio at 22050Hz. ## Training The NeMo toolkit [1] was used for training the model for several epochs. Full training script is [here](https://github.com/bene-ges/nemo_compatible/blob/main/scripts/tts/ru_ipa_fastpitch_hifigan/train.sh). ### Datasets This model is trained on [RUSLAN](https://ruslan-corpus.github.io/) [2] corpus (single speaker, male voice) sampled at 22050Hz. ## References - [1] [NVIDIA NeMo Toolkit](https://github.com/NVIDIA/NeMo) - [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