Digital Audio Processing Tools for Music Corpus Studies

TL;DR

This paper reviews digital audio processing tools and methods for music research, highlighting their capabilities in extracting musical information from audio recordings for corpus analysis.

Contribution

It provides a comprehensive overview of available audio tools and extraction techniques, including both GUI and code-based options, for music corpus studies.

Findings

Summarizes key audio feature extraction methods.

Reviews popular audio processing tools like Audacity and Sonic Visualiser.

Provides background on signal processing relevant to music analysis.

Abstract

Digital audio processing tools offer music researchers the opportunity to examine both non-notated music and music as performance. This chapter summarises the types of information that can be extracted from audio as well as currently available audio tools for music corpus studies. The survey of extraction methods includes both a primer on signal processing and background theory on audio feature extraction. The survey of audio tools focuses on widely used tools, including both those with a graphical user interface, namely Audacity and Sonic Visualiser, and code-based tools written in the C/C++, Java, MATLAB, and Python computer programming languages.