Audio
Coqui TTS
Deep learning toolkit for text-to-speech, battle-tested in research and production
★ 46,1 k étoilesMPL-2.0
Voir le guide →Mozilla TTS est un projet de audio open source, créé par mozilla (mozilla/TTS sur GitHub). Il compte 10 174 étoiles sur GitHub et 1 323 forks, il est publié sous la licence MPL-2.0 et a été mis à jour pour la dernière fois sur GitHub le 9 novembre 2023.
Mozilla's deep-learning text-to-speech library with Tacotron, Glow-TTS and neural vocoders.
Plan for an older environment: the library supports Python >=3.6 and <3.9, and the project has not been updated since late 2023.
For synthesis only, pip install TTS; to train or modify models, clone the repo and install it editable.
List the bundled pretrained models, then choose a text-to-speech model and a vocoder from the list.
Generate speech from the command line with the tts CLI, or write a config.json for your dataset and run a training script such as train_tacotron.py.
Tacotron, Tacotron2, Glow-TTS and SpeedySpeech implementations, with several attention methods including guided attention and Graves attention.
MelGAN, MultiBand-MelGAN, GAN-TTS, ParallelWaveGAN, WaveGrad and WaveRNN vocoders to turn spectrograms into waveforms.
A GE2E speaker encoder computes speaker embeddings efficiently, enabling multi-speaker models and voice conditioning.
Released models in PyTorch, TensorFlow and TFLite formats, plus a tts command-line tool to list models and synthesize speech in one command.
Fast multi-GPU training via distribute.py, detailed console and TensorBoard logs, fine-tuning with --restore_path, and conversion of PyTorch models to TensorFlow/TFLite.
Tools to analyze and curate TTS datasets, a generic dataloader for custom corpora, a demo server for testing models, and benchmarking notebooks.
Clone Mozilla TTS if you plan to train models or work from source.
git clone https://github.com/mozilla/TTS.git
cd TTSInstall from source in editable mode (for synthesis only, pip install TTS is the documented shortcut - use a Python 3.6-3.8 environment).
pip install -e .List the released models, then run the CLI with a model and vocoder name copied from that list.
tts --list_models
tts --text "Text for TTS" --model_name "///" --vocoder_name "///" --out_path output/ # fill in names from --list_modelsIt was developed under Mozilla; the repository has not seen pushes since 2023-11-09, so today it is effectively community-preserved rather than actively maintained.
Yes. It is released under the Mozilla Public License 2.0, which permits use including in commercial products, with file-level copyleft terms.
No. Everything runs locally - pretrained models download once, and training and synthesis happen on your own machine.
Coqui TTS began as the community continuation of this codebase and is the actively maintained successor with newer models; Mozilla TTS is the original library, best for its classic architectures and recipes.
Create a Python 3.8 environment, run pip install TTS, then tts --list_models and synthesize with one of the released models.
Deep learning toolkit for text-to-speech, battle-tested in research and production
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Gratuit et ouvert : récupérez le code source, mettez une étoile au dépôt et commencez à créer.