Mozilla TTS is an open-source library for advanced Text-to-Speech (TTS) generation, targeting researchers and developers seeking high-quality, efficient, and customizable speech synthesis. It offers a robust framework built on state-of-the-art deep learning models, enabling users to train custom voices or leverage pre-trained models across multiple languages.

How It Works

The library implements a modular architecture featuring distinct Text-to-Spectrogram models (Tacotron, Tacotron2, Glow-TTS, Speedy-Speech) and various Vocoder models (MelGAN, ParallelWaveGAN, WaveRNN, etc.). It also includes a Speaker Encoder for efficient speaker embedding extraction. This separation allows for flexible experimentation and optimization of individual components, facilitating the achievement of a balance between training ease, inference speed, and audio quality.

Quick Start & Requirements

• Install via pip: pip install TTS
• For development: git clone https://github.com/mozilla/TTS and pip install -e .
• Requires Python >= 3.6 and < 3.9.
• Official Docker image available.
• Tutorials and examples: TTS/Wiki

Highlighted Details

• Supports multi-speaker TTS and efficient multi-GPU training.
• Enables conversion of PyTorch models to TensorFlow 2.0 and TFLite for inference.
• Provides tools for dataset quality analysis and a demo server for model testing.
• Includes notebooks for extensive model benchmarking and parameter selection.

Maintenance & Community

• Active discussion forum: discourse.mozilla.org/c/tts
• Matrix channel for general discussion.
• Governed by Mozilla's code of conduct.

Licensing & Compatibility

• The repository does not explicitly state a license in the provided README. Compatibility for commercial use or closed-source linking is not specified.

Limitations & Caveats

• The README does not specify a license, which may impact commercial adoption.
• Python version compatibility is limited to < 3.9.