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Implementation of DCTTS with Adversarial Training

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AdvDCTTS (Adversarial Deep Convolutional TTS)

Prerequisite

  • python 3.7
  • pytorch 1.3
  • librosa, scipy, tqdm, tensorboardX

Dataset

Usage

  1. Download the above dataset and modify the path in config.py. And then run the below command. 1st arg: signal prepro, 2nd arg: metadata (train/test split)

    python prepro.py 1 1
    
  2. DCTTS has two models. Firstly, you should train the model Text2Mel. I think that 20k step is enough (for only an hour). But you should train the model more and more with decaying guided attention loss.

    python train.py text2mel <gpu_id>
    
  3. Secondly, train the SSRN with GAN. The outputs of SSRN are many high resolution data. So training SSRN is slower than training Text2Mel

    python gan_train.py <gpu_id>
    
  4. After training, you can synthesize some speech from text.

    python synthesize.py <gpu_id>
    
  5. You can also test ssrn using the ground truth mel spectrograms.

    python test.py <gpu_id>
    

Notes

  • You can get more sharp spectrograms

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