The 2nd edition of An Introduction to Audio Content Analysis has been released. Similar to the 1st edition, it introduces standard base-line approaches to a variety of audio analysis and music information retrieval tasks and provides the reader with a multitude of pointers and references if interested. The second edition of the book is restructured, modernized, and expanded and serves as a comprehensive guide on audio content analysis explaining how signal processing and machine learning approaches can be utilized for the extraction of musical content from audio.
The book itself is accompanied by a range of free resources for learning, teaching, and developing audio analysis systems.
Sample topics covered in “Introduction to Audio Content Analysis” include:
- Digital audio signals and their representation, common time-frequency transforms, audio features
- Pitch and fundamental frequency detection, key and chord
- Representation of dynamics in music and intensity-related features
- Beat histograms, onset and tempo detection, beat histograms, and detection of structure in music, and sequence alignment
- Audio fingerprinting, musical genre, mood, and instrument classification
An invaluable guide for newcomers to audio signal processing and industry experts alike, the book covers a wide range of introductory topics pertaining to music information retrieval and machine listening, allowing students and researchers to quickly gain core holistic knowledge in audio analysis and dig deeper into specific aspects of the field with the help of a large amount of references.
resources
In support not only of the text book itself but also of the wider (research) community, all accompanying resources are free, public, and open source.
source code
- Python implementations of core algorithms from the book
- C++ implementations of core algorithms from the book
- Matlab implementations of core algorithms from the book
- Matlab sources to generate all plots in the book
teaching & learning resources
- PDF slides modularized to match to the textbook structure
- LaTeX sources for slides
- lecture videos (for the 1st edition)
other resources
- list of datasets for music and audio tasks
- list of relevant conference deadlines
about the author
Alexander Lerch is Associate Professor and Associate Dean for Research and Creative Practice at the College of Design, Georgia Institute of Technology. He works on the design and implementation of algorithms for audio content analysis and music information retrieval. Lerch is author of more than 60 peer-reviewed publications on a wide range of topics in audio and music analysis and processing.
Before he joined the faculty at Georgia Tech, he co-founded the company zplane.development, a research-driven company which is a leading provider of advanced music software technology.
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