AdaSpeech 2: Adaptive Text to Speech with Untranscribed Data [WIP]

Unofficial Pytorch implementation of AdaSpeech 2.

Requirements :

All code written in Python 3.6.2 .

• Install Pytorch

Before installing pytorch please check your Cuda version by running following command : nvcc --version

pip install torch torchvision

In this repo I have used Pytorch 1.6.0 for torch.bucketize feature which is not present in previous versions of PyTorch.

• Installing other requirements :

pip install -r requirements.txt

• To use Tensorboard install tensorboard version 1.14.0 seperatly with supported tensorflow (1.14.0)

For Preprocessing :

filelists folder contains MFA (Motreal Force aligner) processed LJSpeech dataset files so you don't need to align text with audio (for extract duration) for LJSpeech dataset. For other dataset follow instruction here. For other pre-processing run following command :

python nvidia_preprocessing.py -d path_of_wavs

For finding the min and max of F0 and Energy

python compute_statistics.py

Update the following in hparams.py by min and max of F0 and Energy

p_min = Min F0/pitch
p_max = Max F0
e_min = Min energy
e_max = Max energy

Training :

[WIP]

Citations :

@misc{chen2021adaspeech,
      title={AdaSpeech: Adaptive Text to Speech for Custom Voice}, 
      author={Mingjian Chen and Xu Tan and Bohan Li and Yanqing Liu and Tao Qin and Sheng Zhao and Tie-Yan Liu},
      year={2021},
      eprint={2103.00993},
      archivePrefix={arXiv},
      primaryClass={eess.AS}
}

@misc{yan2021adaspeech,
      title={AdaSpeech 2: Adaptive Text to Speech with Untranscribed Data}, 
      author={Yuzi Yan and Xu Tan and Bohan Li and Tao Qin and Sheng Zhao and Yuan Shen and Tie-Yan Liu},
      year={2021},
      eprint={2104.09715},
      archivePrefix={arXiv},
      primaryClass={cs.SD}
}