Camel: a lightweight framework for content-based audio and music analysis

Authors:
Chris Sanden;Chad R. Befus;John Z. Zhang
Affiliations:
University of Lethbridge, Lethbridge, AB, Canada;University of Lethbridge, Lethbridge, AB, Canada;University of Lethbridge, Lethbridge, AB, Canada
Venue:
Proceedings of the 5th Audio Mostly Conference: A Conference on Interaction with Sound
Year:
2010

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Abstract

In this paper, we present a brief overview of the design decisions and characteristics of CAMEL (Content-based Audio and Music Extraction Library), an easy-to-use C++ framework developed for content-based audio and music analysis. The framework provides a set of tools that are suitable for a wide range of analysis tasks. At the heart of the framework is a library of feature extraction and segmentation algorithms, which can be exploited for the rapid development and experimentation of content-based audio analysis algorithms and systems. The framework has been successfully applied to various research projects in Music Information Retrieval (MIR).