How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.
Aubio is an audio analysis and digital signal processing library designed for music information retrieval. It provides a suite of tools for extracting musical features, estimating fundamental frequencies, and tracking rhythmic pulses in audio streams. The library specializes in the detection of pitch and beat, enabling the extraction of musical notes and the estimation of overall tempo. It also includes capabilities for automatic onset detection to identify the start of sonic events and the separation of audio signals into percussive transients and steady-state tonal components. The system c
Librosa is a Python audio analysis library and digital signal processing framework. It functions as a feature extraction suite and music information retrieval tool designed to analyze the structural and sonic characteristics of audio signals. The library provides specialized capabilities for music analysis, including dynamic tempo tracking to identify rhythmic pulses and spectral feature extraction to compute harmonic spectra, chroma variants, and onset points. It also serves as a time-series audio processor for synchronizing audio streams. The system covers a broad range of audio processing
This project is a music information retrieval library and research dataset designed for audio feature extraction and music genre classification. It provides a framework for training and evaluating machine learning models that categorize audio tracks into hierarchical genre structures, supported by a collection of open-licensed MP3 tracks and pre-computed features. The project includes a music metadata API client to fetch structured track, album, and artist information from external data sources. It utilizes these external integrations to map parent-child relationships between genres and organ
Muzic is a deep learning platform and framework for AI-driven music analysis, composition, and synthesis. It functions as a music generation framework and analysis tool, utilizing large language models and autonomous agents to orchestrate the creation and interpretation of symbolic and audio music. The project is distinguished by its cross-modal capabilities, mapping natural language and symbolic music into a shared joint embedding space for zero-shot classification and information retrieval. It employs a variety of specialized architectures, including diffusion frameworks for audio synthesis
Python audio and music signal processing library
The main features of cpjku/madmom are: Computer Audition, Music Information Retrieval.
Projects with overlapping indexed features include: aubio/aubio — Aubio is an audio analysis and digital signal processing library designed for music information retrieval. It provides… librosa/librosa — Librosa is a Python audio analysis library and digital signal processing framework. It functions as a feature… music-and-culture-technology-lab/omnizart — Omnizart is a deep learning framework designed for automatic music transcription and music information retrieval. It… mdeff/fma — This project is a music information retrieval library and research dataset designed for audio feature extraction and… microsoft/muzic — Muzic is a deep learning platform and framework for AI-driven music analysis, composition, and synthesis. It functions… bytedance/music_source_separation — This project is a deep learning toolkit designed for audio source separation and music information retrieval. It…