This is a very well-written and well-presented book. It differs from some other books on signal processing, which use MATLAB as the main vehicle for conveying practical solutions, as it doesn’t clutter all its pages with MATLAB code listings. MATLAB code, though an essential part of the book, and available for download, is only briefly explained, as in every good manual. The book deals less with signal processing techniques, which are covered only in the first couple of chapters after the introduction, than with pattern recognition and machine learning. Indeed, the emphasis is placed on classification and recognition algorithms.

In far fewer pages than in other works dedicated to these topics, the authors clearly present the practical details of major classification and pattern search algorithms, such as k-means, dynamic programming, and hidden Markov. The only unfortunate omission among these select algorithms is an introduction to the most popular type of neural network (NN), backpropagation NN. Hopefully, they will include it in a future edition, since by application base, it is almost as widespread as the selected ones in the book.

The book also presents some issues in music information retrieval, which while interesting are of lesser value. The MATLAB toolbox for that purpose, music information retrieval (MIR), has been available for many years now, with very extensive documentation.

This new book on audio content analysis and the associated toolbox is highly recommended to audio signal processing practitioners. It can even serve as a first introduction to the more general area of pattern classification.