dongheehand / Tacotron-PyTorch

PyTorch implementation of Tacotron

Tacotron

An implementation of Tacotron described in the paper using pytorch. Tacotron: Towards End-to-End Speech Synthesis

Published in INTERSPEECH 2017

Requirement

• torch 1.3.0
• falcon 1.2.0
• inflect 0.2.5
• librosa 0.5.1
• numpy 1.13.3
• scipy 1.0.0
• Unidecode 0.4.21
• pandas 0.21.0

Datasets

• LJ-Speech (English)
• KSS-dataset (Korean)

Pre-trained model

• LJ-Speech(English)
• KSS-dataset(Korean)

Model training

Train using LJ-Speech dataset

python train.py

Train using KSS-dataset

1. Change options in hyperparams.py

• cleaners option (26-th line) : from 'english_cleaners' to 'korean_cleaners'
• dataset option (29-th line) : from 'LJSpeech' to 'KSS'
• data_path option (30-th line)

2. Change the sample sentences for generating TTS wav files from english to korean during training. (xx-th line in train.py)

python train.py

Tensorboard

• You can see the train loss graph.
• Furthermore, you can listen to generated wav files during training.

Loss	wav_files

tensorboard --logdir=runs

Generate TTS wav files

1. Download pre-trained model.

• LJ-Speech(English)
• KSS-dataset(Korean)

2. Change option in hyperparams.py

• If you want to generate english wav files, cleaners option (26-th line) should be 'english_cleaners'
• And if you want to generate korean wav files, cleaners option (26-th line) should be 'korean_cleaners'

3. Generate TTS wav files

python eval.py --checkpoint_path ./pre_trained_model_path

Experimental Results

Train loss

LJ-Speech	KSS

TTS wav files

LJ-results(English)

KSS-results(korean)

Comments

If you have any questions or comments on my codes, please email to me. [e-mail]

Reference

[1] https://github.com/soobinseo/Tacotron-pytorch

[2] https://github.com/hccho2/Tacotron-Wavenet-Vocoder-Korean