Blaizzy/mlx-audio
Jun 2026 – Jun 2026
1 Month active
Languages Used
No languages
Technical Skills
Audio ProcessingDigital Signal ProcessingMLXMachine LearningNumPyPython
Alazar Manakelew
PROFILE
Alazar Manakelew
Developed and enhanced the mlx-audio repository by delivering three new features focused on speech-to-text and audio processing pipelines. Work included integrating the Higgs-Audio v3 STT model with Voice Activity Detection chunking, enabling more accurate and configurable audio segmentation. Implemented a native MLX-based audio feature extractor in Python and NumPy, replacing external dependencies for spectrogram computation and improving maintainability. Updated documentation to guide users on MLX-ready model weights and streamlined loading via Hugging Face tools. Emphasized reliability and test coverage, ensuring outputs remained byte-identical to references and reducing external dependencies for faster, more robust deployment across teams.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
4Total
Bugs
0
Commits
4
Features
3
Lines of code
1,105
Activity Months1
Your Network
77 peopleWork History
June 2026
4 Commits • 3 Features
Jun 1, 2026June 2026 performance summary for Blaizzy/mlx-audio: Delivered end-to-end STT and audio feature pipeline enhancements with a strong emphasis on reliability, maintainability, and business value. Key features were implemented with a native audio processing path, improved configuration management, and updated documentation to facilitate broader adoption and smoother deployments across teams.
4 Commits • 3 Features
Jun 1, 2026June 2026 performance summary for Blaizzy/mlx-audio: Delivered end-to-end STT and audio feature pipeline enhancements with a strong emphasis on reliability, maintainability, and business value. Key features were implemented with a native audio processing path, improved configuration management, and updated documentation to facilitate broader adoption and smoother deployments across teams.
June 2026
Activity
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Quality Metrics
Correctness100.0%
Maintainability100.0%
Architecture95.0%
Performance85.0%
AI Usage75.0%
Skills & Technologies
Programming Languages
No languages yet
Technical Skills
Audio ProcessingDigital Signal ProcessingMLXMachine LearningNumPyPythonSpeech-to-Textdeep_learningdocumentationhuggingfacemachine learningmachine_learningmlxnumpypython
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