ISTE/John Wiley, 2012. — 260 p.The growing amount of audio and music data on the Internet and in user databases leads to an increasing need for intelligent browsing, retrieving, and processing of this data with automated methods. Audio content analysis, a subfield of the research field music information retrieval, aims at extracting (musical and perceptual) properties directly from the audio signal to support these tasks. Knowledge of these properties allows us to improve the interaction of humans or machines with digital audio signals. It enables new ways of assessing, processing, and visualizing music. Although analysis of audio signals covers other research areas such as automatic speech recognition, we will restrict ourselves to the analysis of music signals in the context of this book. When preparing classes on audio content analysis with a focus on music recordings it became quickly clear that — although there is a vast and growing amount of research literature available — there exists no introductory literature. This observation led to writing this book in the hope it might assist students, engineers, and developers who have basic knowledge of digital signal processing. The focus lies on the signal processing part of audio content analysis, but wherever it may improve the understanding of either algorithmic design choices or implementation details some basic characteristics of human perception, music theory, and notation as well as machine learning will be summarizedIntroduction Fundamentals Instantaneous Features Intensity Tonal Analysis Temporal Analysis Alignment Musical Genre, Similarity, and Mood Audio Fingerprinting Music Performance Analysis
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