metadata
license: cc-by-4.0
language:
- ru
library_name: nemo
How to use
See example in this notebook. It contains the inference pipeline for G2P + FastPitch + Hifigan.
Input
This model expects text converted to IPA-like transcriptions. See this g2p model for conversion of plain Russian text to phonemes. If you feed plain text directly, it will work, but quality will be low.
Output
This model generates mel spectrograms.
Training
The NeMo toolkit [1] was used for training the model for 1000+ epochs.
Datasets
This model is trained on RUSLAN [2] corpus (single speaker, male voice) sampled at 22050Hz.
References
- [1] NVIDIA NeMo Toolkit
- [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