{"data":{"slug":"blaizzy-mlx-audio","name":"mlx-audio","tagline":"A text-to-speech (TTS), speech-to-text (STT) and speech-to-speech (STS) library on Apple's MLX framework.","github_url":"https://github.com/Blaizzy/mlx-audio","owner":"Blaizzy","repo":"mlx-audio","owner_avatar_url":"https://avatars.githubusercontent.com/u/23445657?v=4","primary_language":"Python","stars":7914,"forks":722,"topics":["apple-silicon","audio-processing","mlx","multimodal","speech-recognition","speech-synthesis","speech-to-text","text-to-speech","transformers"],"archived":false,"github_pushed_at":"2026-09-18T21:23:53+00:00","maintenance_label":"Very active","stars_delta_30d":275,"url":"https://www.graphcanon.com/tools/blaizzy-mlx-audio","markdown_url":"https://www.graphcanon.com/tools/blaizzy-mlx-audio.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/blaizzy-mlx-audio","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=blaizzy-mlx-audio","description":"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.","homepage_url":"https://blaizzy.github.io/mlx-audio/","license":"MIT","open_issues":107,"watchers":55,"ai_summary":"The mlx-audio repository offers advanced speech processing functionalities including TTS, STT, and STS operations leveraging the efficiency of the MLX framework specifically for tasks involving audio data on Apple Silicon Macs. Requires Python 3.10+, Apple Silicon support, MLX framework installation, and ffmpeg for various audio formats.","readme_excerpt":"### Using uv to install only the command line tools\nLatest release from pypi:\n```bash\nuv tool install --force mlx-audio --prerelease=allow\n```\n\nLatest code from github:\n```bash\nuv tool install --force git+https://github.com/Blaizzy/mlx-audio.git --prerelease=allow\n```\n\n---\n\n## Requirements\n\n- Python 3.10+\n- Apple Silicon Mac (M1/M2/M3/M4)\n- MLX framework\n- **ffmpeg** (required for MP3/FLAC/OGG/Opus/Vorbis audio encoding)","github_created_at":"2024-11-27T21:14:34+00:00","created_at":"2026-07-11T12:05:59.414899+00:00","updated_at":"2026-09-20T07:05:14.299283+00:00","categories":[{"slug":"speech-audio","name":"Speech & Audio","url":"https://www.graphcanon.com/categories/speech-audio","markdown_url":"https://www.graphcanon.com/categories/speech-audio.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/speech-audio"}],"tags":[{"slug":"apple-silicon","name":"apple-silicon"},{"slug":"audio-processing","name":"audio-processing"},{"slug":"mlx","name":"mlx"},{"slug":"multimodal","name":"multimodal"},{"slug":"speech-recognition","name":"speech recognition"},{"slug":"speech-synthesis","name":"speech-synthesis"},{"slug":"speech-to-text","name":"speech-to-text"},{"slug":"text-to-speech","name":"text-to-speech"}],"trust":{"provenance":{"is_fork":false,"github_id":895253710,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-09-20T07:05:11.962Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":9,"days_since_push":1,"last_release_at":"2026-09-14T15:25:36Z","stars_delta_30d":275,"open_issues_delta_30d":19},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T12:06:00.965Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-09-20T07:05:13.015Z"},"has_cli":{"value":true,"source":"pyproject.toml:[project.scripts]","observed_at":"2026-09-20T07:05:13.015Z"},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-09-20T07:05:13.015Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-09-20T07:05:13.015Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["Use mlx-audio if you require high performance in text-to-speech, speech-to-text, or speech-to-speech transformations specifically optimized for Apple Silicon Macs (M1/M2/M3/M4).","If your project's development environment is Python 3.10+ and you need support for multiple audio formats including MP3, FLAC, Ogg, Opus, and Vorbis using ffmpeg.","Consider mlx-audio when working within the MLX framework context, as it integrates closely with this ecosystem to improve efficiency in speech processing tasks."],"when_not_to_use":["Do not use mlx-audio if your project or target hardware is not based on Apple Silicon. It requires specifically designed optimizations that do not apply to Intel processors.","Avoid mlx-audio when the dependency on ffmpeg for audio format handling becomes a limitation due to licensing, compatibility with existing pipelines, or specific codec requirements.","Do not opt for mlx-audio if your application does not require seamless integration within the MLX framework and does not gain any significant benefit from its specialized support."],"source":"enrich:decision_facts","observed_at":"2026-07-17T13:05:02.572Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"mlx-audio is designed to offer an efficient speech processing library on Apple's MLX framework for tasks involving TTS, STT, and STS operations."}]}}