mlx-audio
A text-to-speech (TTS), speech-to-text (STT) and speech-to-speech (STS) library built on Apple's MLX framework, providing efficient speech analysis on Apple Silicon.
💡 Why It Matters
The mlx-audio repository addresses key challenges in speech processing by providing a robust library for text-to-speech (TTS), speech-to-text (STT), and speech-to-speech (STS) applications. This open source tool is particularly beneficial for ML/AI teams looking to implement efficient speech analysis on Apple Silicon. With a maturity level that indicates it's production-ready, engineers can confidently integrate it into their workflows. However, it may not be suitable for projects that require cross-platform compatibility or those needing extensive customisation beyond the provided functionalities.
🎯 When to Use
This library is a strong choice when developing applications that require high-performance speech processing on Apple Silicon. Teams should consider alternatives if they need broader platform support or specific features not covered by mlx-audio.
👥 Team Fit & Use Cases
Roles such as machine learning engineers, data scientists, and software developers can effectively utilise mlx-audio in their projects. It is commonly integrated into products like virtual assistants, automated transcription services, and interactive voice response systems.
🎭 Best For
🏷️ Topics & Ecosystem
📊 Activity
Latest commit: 2026-02-11. Activity data is based on daily RepoPi snapshots of the GitHub repository.