Machine Learning

Multi-Speaker Adaptive Text-to-Speech Generation with python

StyleSpeech

PyTorch Implementation of Meta-StyleSpeech : Multi-Speaker Adaptive Text-to-Speech Generation.

model_1

  • [x] StyleSpeech (naive branch)
  • [x] Meta-StyleSpeech (main branch)

Dependencies

You can install the Python dependencies with

pip3 install -r requirements.txt

Inference

You have to download pretrained models and put them in output/ckpt/LibriTTS/.

For English single-speaker TTS, run

python3 synthesize.py --text "YOUR_DESIRED_TEXT" --ref_audio path/to/reference_audio.wav --restore_step 200000 --mode single -p config/LibriTTS/preprocess.yaml -m config/LibriTTS/model.yaml -t config/LibriTTS/train.yaml

The generated utterances will be put in output/result/. Your synthesized speech will have ref_audio‘s style.

Batch Inference

Batch inference is also supported, try

python3 synthesize.py --source preprocessed_data/LibriTTS/val.txt --restore_step 200000 --mode batch -p config/LibriTTS/preprocess.yaml -m config/LibriTTS/model.yaml -t config/LibriTTS/train.yaml

to synthesize all utterances in preprocessed_data/LibriTTS/val.txt. This can be viewed as a reconstruction of validation datasets referring to themselves

 

 

 

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