Scientific Audio

repo: faroit/awesome-python-scientific-audio
category: Programming Languages


Python for Scientific Audio

Awesome Build Status

The aim of this repository is to create a comprehensive, curated list of python software/tools related and used for scientific research in audio/music applications.

Contents

  • Total number of packages: 66

Read-Write

Transformations - General DSP

Feature extraction

Data augmentation

Speech Processing

Environmental Sounds

Perceptial Models - Auditory Models

Source Separation

Music Information Retrieval

Deep Learning

Symbolic Music - MIDI - Musicology

Realtime applications

Web Audio

Audio Dataset and Dataloaders

Wrappers for Audio Plugins

Tutorials

Books

  • [Python Data Science Handbook](https://github.com/jakevdp/PythonDataScienceHandbook) - Jake Vanderplas, Excellent Book and accompanying tutorial notebooks.
  • [Fundamentals of Music Processing](https://www.audiolabs-erlangen.de/fau/professor/mueller/bookFMP) - Meinard Müller, comes with Python exercises.

Scientific Papers

  • Python for audio signal processing - John C. Glover, Victor Lazzarini and Joseph Timoney, Linux Audio Conference 2011.
  • [librosa: Audio and Music Signal Analysis in Python](http://conference.scipy.org/proceedings/scipy2015/pdfs/brian_mcfee.pdf), Video - Brian McFee, Colin Raffel, Dawen Liang, Daniel P.W. Ellis, Matt McVicar, Eric Battenberg, Oriol Nieto, Scipy 2015.
  • pyannote.audio: neural building blocks for speaker diarization, Video - Hervé Bredin, Ruiqing Yin, Juan Manuel Coria, Gregory Gelly, Pavel Korshunov, Marvin Lavechin, Diego Fustes, Hadrien Titeux, Wassim Bouaziz, Marie-Philippe Gill, ICASSP 2020.

Other Resources

There is already PythonInMusic but it is not up to date and includes too many packages of special interest that are mostly not relevant for scientific applications. Awesome-Python is large curated list of python packages. However, the audio section is very small.

Contributing

Your contributions are always welcome! Please take a look at the contribution guidelines first.

I will keep some pull requests open if I'm not sure whether those libraries are awesome, you could vote for them by adding 👍 to them.

License

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