An Introduction to Audio Content Analysis describes standard approaches to various signal processing tasks required for the design of Music Information Retrieval (MIR) systems.
The text book categorizes audio content into four classes (tonal, temporal, timbral, intensity-related) and outlines ways to extract characteristics for each individual category, for instance, fundamental frequency, tempo, timbre features, and audio level. The remaining chapters introduce systems for more complex tasks such as audio-to-audio-alignment, genre and mood recognition, and audio fingerprinting. It closes with an overview of music performance analysis as an example for applying audio content analysis in a research context.
Targeted at engineers, graduate students, and programmers with basic knowledge of signal processing, the book describes various analysis algorithms with their theoretical, technical, and perceptual background and guides the reader by presenting various analysis approaches to the same task.
about the author
Alexander Lerch works on the design and implementation of algorithms for audio content analysis and music information retrieval. In the past, he worked on audio signal processing algorithms such as time scaling, audio effects, key analysis, etc. In the year 2000, he co-founded the company zplane.development. This research-driven company with a close relationship to the Technical University of Berlin (Audio Communications Group) is today the leading licensor of advanced music software technology.
He joined the faculty of the Georgia Tech Center for Music Technology, where he leads the Music Informatics Group, in the year 2013 as Assistant Professor.