Skip to content

Released Models

Eren Gölge edited this page Jan 12, 2021 · 41 revisions

English

TTS Models Dataset Commit Audio Sample Details
Tacotron2 LJSpeech branch --- Details
Tacotron2 DDC LJSpeech 72a6ac5 voice samples Trained with DDC and includes PyTorch, Tensorflow and TFLite models. Check Colab notebooks or notebooks folder.
Glow-TTS LJSpeech 08394e4 --- Details. Sample notebook
Multi-Speaker-Tacotron2 VCTK 4873601 Colab notebook Multi-Speaker TTS model with Tacotron2/
Multi-Speaker-Tacotron2 DDC VCTK 2136433 Colab notebook Multi-Speaker TTS model with Tacotron2 and Double Decoder Consistency.
Tacotron2 with Dynamic Conv Attention LJSpeech 4132240 Colab notebook Tacotron2 with Dynamic Convolutional Attention.
Glow-TTS LJSpeech 4132240 Colab notebook Glow-TTS as in the paper.

Speaker Encoder Models Dataset Commit
Speaker-Encoder-iter25k LibriSpeech ...
Speaker-Encoder by @mueller91 LibriTTS + VCTK + VoxCeleb + CommonVoice ...

Vocoder Models Dataset Commit Details
ParallelWaveGAN LJSpeech 72a6ac5 Trained using TTS.vocoder. It produces better results than MelGAN model but it is slightly slower. Check notebooks for testing.
Multi-Band MelGAN LJSpeech 72a6ac5 Trained using TTS.vocoder. It is the fastest vocoder model. Check notebooks for testing.
WaveRNN models go to repo for the models. (Soon to be deprecated)
Full-Band MelGAN LibriTTS c514628 Trained using TTS.vocoder. Generic vocoder that can sample any voice. Sampling rate 24Khz. To use with a different sampling rate follow this issue.
Universal WaveGrad LibriTTS 2136433 Trained using TTS.vocoder. Generic vocoder that can sample any voice. Original Sampling rate 24Khz. To use with a different sampling rate follow this issue.

Simple packaging - self-contained package that runs an HTTP API for a pre-trained TTS model

How to use:

  1. Create a fresh virtual environment with Python 3.6
  2. $ apt-get install espeak libsndfile1
  3. $ pip install python_package_url_from_table_below
  4. $ python -m TTS.server.server
  5. Open http://localhost:5002
Model Dataset Python package nginx/uWSGI config files
Tacotron 2 + Forward Attention + PWGAN LJSpeech TTS-0.0.1+92aea2a-py3-none-any.whl tts-nginx-uwsgi.zip

The server is a Flask application. For deployment with multiple workers see the nginx/uWSGI config files also linked in the table above. Pass --use_cuda 1 to use GPUs when available.


Spanish

TTS Models Dataset Commit Audio Sample Details
Tacotron2 DDC MAI-Labs 48a40c4 --- Model Details and Colab Notebook.

French

TTS Models Dataset Commit Audio Sample Details
Tacotron2 DDC MAI-Labs f09defa --- Model Details and Colab Notebook.

German

German Model Colab Example


Portuguese

model details by @Edresson