This is a repository for an unofficial implementation of the Tacotron speech synthesis model using PyTorch. Tacotron is a model that converts given text into a spectrogram and then uses the Griffin-Lim algorithm to synthesize speech. For more detailed information, please refer to here.
The implementation is still in progress.
All implementations were carried out on a container utilizing a PyTorch-based Docker image. There is no need to download a separate dataset, as the torchaudio package is used to automatically download the LJSpeech-1.1 dataset.
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Prepare docker image / container
docker pull pytorch/pytorch:2.3.0-cuda12.1-cudnn8-runtime -
Install requirements
pip install -r requirements.txt
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Start training
python train.py
[1] Wang, Yuxuan, et al. "Tacotron: Towards end-to-end speech synthesis." arXiv preprint arXiv:1703.10135 (2017).
[2] https://github.com/r9y9/tacotron_pytorch
[3] https://github.com/Kyubyong/tacotron
[4] Keith Ito and Linda Johnson, The LJ Speech Dataset, https://keithito.com/LJ-Speech-Dataset/, 2017