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All Projects → tugstugi → Pytorch Dc Tts

tugstugi / Pytorch Dc Tts

Licence: mit
Text to Speech with PyTorch (English and Mongolian)

Programming Languages

python
139335 projects - #7 most used programming language

Labels

jupyter-notebookdeep-learningpytorchconvolutional-neural-networkstext-to-speechttsspeech-synthesis

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PyTorch implementation of Efficiently Trainable Text-to-Speech System Based on Deep Convolutional Networks with Guided Attention based partially on the following projects:

Online Text-To-Speech Demo

The following notebooks are executable on https://colab.research.google.com :

For audio samples and pretrained models, visit the above notebook links.

Training/Synthesizing English Text-To-Speech

The English TTS uses the LJ-Speech dataset.

  1. Download the dataset: python dl_and_preprop_dataset.py --dataset=ljspeech
  2. Train the Text2Mel model: python train-text2mel.py --dataset=ljspeech
  3. Train the SSRN model: python train-ssrn.py --dataset=ljspeech
  4. Synthesize sentences: python synthesize.py --dataset=ljspeech
    • The WAV files are saved in the samples folder.

Training/Synthesizing Mongolian Text-To-Speech

The Mongolian text-to-speech uses 5 hours audio from the Mongolian Bible.

  1. Download the dataset: python dl_and_preprop_dataset.py --dataset=mbspeech
  2. Train the Text2Mel model: python train-text2mel.py --dataset=mbspeech
  3. Train the SSRN model: python train-ssrn.py --dataset=mbspeech
  4. Synthesize sentences: python synthesize.py --dataset=mbspeech
    • The WAV files are saved in the samples folder.
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