All Projects → h-meru → Tacotron Wavernn

h-meru / Tacotron Wavernn

Licence: mit
TTS (Tacotron + WaveRNN)

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Tacotron-WaveRNN

Tacotron + WaveRNN synthesis

Makes use of:

You'll at least need python3, PyTorch 0.4.1, Tensorflow and librosa.

Preprocess

python3 preprocess.py --model='WaveRNN'

Default parameters:

name default
--base_dir
--hparams ex) 'wavernn_gpu_num=4, wavernn_batch_size=16'
--model 'Tacotron' 'Tacotron', 'WaveRNN'
--dataset 'LJSpeech-1.1' 'LJSpeech-1.0', 'LJSpeech-1.1', 'M-AILABS'

Others, look at this file...

Training

python3 train.py --model='Tacotron-2' --GTA --use_cuda

If you would like to train separately...

# Tacotron
python3 train.py --model='Tacotron'

# Tacotron synth
python3 synthesize.py --model='Tacotron' --mode='synthesis' --GTA

# WaveRNN
python3 train.py --model='WaveRNN' --use_cuda

Default parameters:

name default
--base_dir
--hparams ex) 'wavernn_gpu_num=4, wavernn_batch_size=16'
--model 'Tacotron-2' 'Tacotron-2', 'Tacotron', 'WaveRNN'
--mode 'synthesis' 'eval', 'synthesis', 'live'
--init False True, False
--slack_url {your slack wabhook url...}
--use_cuda False True, False

Others, look at this file...

Synthesis

python3 synthesize.py --model='Tacotron-2' --text_list={your text file}

Default parameters:

name default
--base_dir
--hparams ex) 'wavernn_gpu_num=4, wavernn_batch_size=16'
--model 'Tacotron-2' 'Tacotron-2', 'Tacotron', 'WaveRNN'
--mode 'eval' 'eval', 'synthesis', 'live'
--text_list {your text file...}
--use_cuda False True, False

Others, look at this file...

Pretrained Model(old)

https://github.com/h-meru/Tacotron-WaveRNN/files/2444777/wavernn_model.zip

Samples(old)

https://github.com/h-meru/Tacotron-WaveRNN/files/2444792/Samples_730k.zip

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