mehdihosseinimoghadam / Catalan-Text-to-Speech

Catalan Text to Speech

Home Page:https://mehdihosseinimoghadam.github.io//posts/2022/04/Catalan-Text-To-Speech/

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Catalan Text to Speech

Based on Microsoft's FastSpeech

Catalan Version of FastSpeech Repo

fast_speech


model

The model has following advantages:

  • Robustness: No repeats and failed attention modes for challenging sentences.
  • Speed: The generation of a mel spectogram takes about 0.04s on a GeForce RTX 2080.
  • Controllability: It is possible to control the speed of the generated utterance.
  • Efficiency: In contrast to FastSpeech and Tacotron, the model of ForwardTacotron does not use any attention. Hence, the required memory grows linearly with text size, which makes it possible to synthesize large articles at once.

Check out the latest audio samples (ForwardTacotron + WaveRNN)!

🔈 Samples

Can be found here.

The samples are generated with a model trained on 2 hoours of data from Catalan Common Voice and vocoded with WaveRNN, MelGAN, or HiFiGAN. You can try out the latest pretrained model with the following notebook:

Open In Colab

References

Acknowlegements

Maintainers

Copyright

See LICENSE for details.