Coqui STT (🐸STT) is a deep learning toolkit for training and deploying speech-to-text (STT) models, designed for both production and research use. It offers high-quality pre-trained models, an efficient multi-GPU training pipeline, streaming inference, and real-time capabilities with small acoustic model footprints.

How It Works

🐸STT leverages deep learning architectures for its STT models, enabling efficient training and deployment. Its design prioritizes speed and a small model footprint, making it suitable for resource-constrained environments. The toolkit supports multi-GPU training for faster model development and offers streaming inference for real-time applications.

Quick Start & Requirements

Installation and usage details are available in the official documentation: stt.readthedocs.io.

Highlighted Details

• Battle-tested in production and research environments.
• Supports multiple transcripts with associated confidence scores.
• Provides bindings for various programming languages.
• Offers streaming and real-time inference capabilities.

Maintenance & Community

This project is no longer actively maintained, and the online Model Zoo has been discontinued. The focus has shifted to newer STT models like Whisper and Coqui TTS/Studio. Models remain available in the coqui-ai/STT-models repository. Community support is available via GitHub Discussions and a Gitter Room.

Licensing & Compatibility

The specific license is not explicitly stated in the provided README snippet, but it is an open-source project. Compatibility for commercial use or closed-source linking would require further investigation into the licensing terms of the models and codebase.

Limitations & Caveats

The project is explicitly stated as no longer actively maintained, with the online Model Zoo shut down. This indicates a lack of ongoing development, bug fixes, and feature additions, potentially posing risks for long-term adoption or reliance.