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mozilla/TTS

A deep learning library for advanced Text-to-Speech generation, offering high-quality speech synthesis with pretrained models and multi-language support.

Core Features

High-performance Deep Learning models for Text2Speech (Tacotron, Glow-TTS, etc.) and Vocoders (MelGAN, WaveRNN, etc.).

Support for multi-speaker TTS and efficient Multi-GPUs training.

Tools for dataset curation and conversion of PyTorch models to Tensorflow/TFLite.

Pretrained models available in 20+ languages.

Modular codebase for easy experimentation and development.

Quick Start

tts --text "Hello world" --model_name "tts_models/en/ljspeech/tacotron2-DDC" --out_path "output.wav"

Detailed Introduction

Mozilla TTS is an advanced open-source library for Text-to-Speech (TTS) generation, leveraging the latest deep learning research. It's engineered for an optimal balance of training ease, speed, and output quality. The project provides a comprehensive suite of models, including Text2Spec and Vocoder architectures, along with tools for dataset analysis. With support for over 20 languages, multi-speaker capabilities, and efficient multi-GPU training, TTS is widely adopted in both product development and research, offering a robust foundation for building high-quality speech synthesis applications.