Coqui TTS - AI Audio Tools Tool

Overview

Coqui TTS is an open-source deep learning toolkit for high-quality text-to-speech synthesis, offering a balance of research flexibility and production-ready features. The project provides pretrained models across a wide range of languages and voices, tools to train and fine-tune models on custom datasets, and utilities for dataset analysis and audio preprocessing. According to the GitHub repository, the project maintains a model catalog and community-contributed checkpoints that simplify getting started with synthesis or voice cloning. Coqui TTS implements multiple state-of-the-art neural architectures (examples include VITS, Tacotron2, FastSpeech2, and Glow-TTS) and pairs them with neural vocoders such as HiFi-GAN and MelGAN. It exposes both a Python API and a command-line interface for inference, training, and export workflows, and includes export paths to production formats like TorchScript and ONNX. The toolkit is intended for use in research experiments as well as deployment scenarios where low-latency, high-fidelity TTS is required (see the GitHub repository for model-specific performance and usage details).

Installation

Install via pip:

pip install TTS

pip install git+https://github.com/coqui-ai/TTS.git

git clone https://github.com/coqui-ai/TTS.git && cd TTS && pip install -e .

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

Key Features

• Pretrained models across 1100+ languages and many voices, hosted via the project model catalog
• Support for modern TTS architectures: VITS, Tacotron2, FastSpeech2, Glow-TTS
• Integrated neural vocoders such as HiFi-GAN and MelGAN for high-fidelity audio
• Python API and CLI for training, fine-tuning, inference, and batch synthesis
• Export options to TorchScript and ONNX for optimized production deployments

Community

Coqui TTS is maintained openly on GitHub with an active issue tracker, community model contributions, and regular commits. The project publishes community checkpoints and model recipes that simplify fine-tuning and multilingual experiments. Community support and discussion occur via the repository issues, community channels referenced on the project pages, and contributed examples and notebooks. For up-to-date release notes, models, and platform-specific instructions, consult the official GitHub repository and the project's community links.

Key Information

• Category: Audio Tools
• Type: AI Audio Tools Tool