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๐Ÿธ๐Ÿ’ฌ - a deep learning toolkit for Text-to-Speech, battle-tested in research and production

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๐ŸธTTS is a library for advanced Text-to-Speech generation. It's built on the latest research, was designed to achieve the best trade-off among ease-of-training, speed and quality. ๐ŸธTTS comes with pretrained models, tools for measuring dataset quality and already used in 20+ languages for products and research projects.

GithubActions License Docs PyPI version Covenant Downloads Gitter DOI

๐Ÿ“ฐ Subscribe to ๐ŸธCoqui.ai Newsletter

๐Ÿ“ข English Voice Samples and SoundCloud playlist

๐Ÿ“„ Text-to-Speech paper collection

๐Ÿ’ฌ Where to ask questions

Please use our dedicated channels for questions and discussion. Help is much more valuable if it's shared publicly so that more people can benefit from it.

Type Platforms
๐Ÿšจ Bug Reports GitHub Issue Tracker
๐ŸŽ Feature Requests & Ideas GitHub Issue Tracker
๐Ÿ‘ฉโ€๐Ÿ’ป Usage Questions Github Discussions
๐Ÿ—ฏ General Discussion Github Discussions or Gitter Room

๐Ÿ”— Links and Resources

Type Links
๐Ÿ’ผ Documentation ReadTheDocs
๐Ÿ’พ Installation TTS/README.md
๐Ÿ‘ฉโ€๐Ÿ’ป Contributing CONTRIBUTING.md
๐Ÿ“Œ Road Map Main Development Plans
๐Ÿš€ Released Models TTS Releases and Experimental Models

๐Ÿฅ‡ TTS Performance

Underlined "TTS*" and "Judy*" are ๐ŸธTTS models

Features

  • High-performance Deep Learning models for Text2Speech tasks.
    • Text2Spec models (Tacotron, Tacotron2, Glow-TTS, SpeedySpeech).
    • Speaker Encoder to compute speaker embeddings efficiently.
    • Vocoder models (MelGAN, Multiband-MelGAN, GAN-TTS, ParallelWaveGAN, WaveGrad, WaveRNN)
  • Fast and efficient model training.
  • Detailed training logs on the terminal and Tensorboard.
  • Support for Multi-speaker TTS.
  • Efficient, flexible, lightweight but feature complete Trainer API.
  • Ability to convert PyTorch models to Tensorflow 2.0 and TFLite for inference.
  • Released and read-to-use models.
  • Tools to curate Text2Speech datasets underdataset_analysis.
  • Utilities to use and test your models.
  • Modular (but not too much) code base enabling easy implementation of new ideas.

Implemented Models

Text-to-Spectrogram

Attention Methods

  • Guided Attention: paper
  • Forward Backward Decoding: paper
  • Graves Attention: paper
  • Double Decoder Consistency: blog
  • Dynamic Convolutional Attention: paper

Speaker Encoder

Vocoders

You can also help us implement more models.

Install TTS

๐ŸธTTS is tested on Ubuntu 18.04 with python >= 3.6, < 3.9.

If you are only interested in synthesizing speech with the released ๐ŸธTTS models, installing from PyPI is the easiest option.

pip install TTS

By default, this only installs the requirements for PyTorch. To install the tensorflow dependencies as well, use the tf extra.

pip install TTS[tf]

If you plan to code or train models, clone ๐ŸธTTS and install it locally.

git clone https://github.com/coqui-ai/TTS
pip install -e .[all,dev,notebooks,tf]  # Select the relevant extras

If you are on Ubuntu (Debian), you can also run following commands for installation.

$ make system-deps  # intended to be used on Ubuntu (Debian). Let us know if you have a diffent OS.
$ make install

If you are on Windows, ๐Ÿ‘‘@GuyPaddock wrote installation instructions here.

Directory Structure

|- notebooks/       (Jupyter Notebooks for model evaluation, parameter selection and data analysis.)
|- utils/           (common utilities.)
|- TTS
    |- bin/             (folder for all the executables.)
      |- train*.py                  (train your target model.)
      |- distribute.py              (train your TTS model using Multiple GPUs.)
      |- compute_statistics.py      (compute dataset statistics for normalization.)
      |- convert*.py                (convert target torch model to TF.)
      |- ...
    |- tts/             (text to speech models)
        |- layers/          (model layer definitions)
        |- models/          (model definitions)
        |- tf/              (Tensorflow 2 utilities and model implementations)
        |- utils/           (model specific utilities.)
    |- speaker_encoder/ (Speaker Encoder models.)
        |- (same)
    |- vocoder/         (Vocoder models.)
        |- (same)

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๐Ÿธ๐Ÿ’ฌ - a deep learning toolkit for Text-to-Speech, battle-tested in research and production

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