Structural Analysis and Segmentation of Music Signals

Bee Suan Ong
University Pompeu Fabra, Barcelona, Spain (February, 2007)


With the recent explosion in the quantity of digital audio libraries and databases, content descriptions play an important role in efficiently managing and retrieving audio files. This doctoral research aims to discover and extract structural description from polyphonic music signals. As repetition and transformations of music structure creates a unique identity of music itself, extracting such information can link low-level and higher-level descriptions of music signal and provide better quality access plus powerful way of interacting with audio content. Finding appropriate boundary truncations is indispensable in certain content-based applications. Thus, temporal audio segmentation at the semantic level and the identification of representative excerpts from music audio signal are also investigated. We make use of higher-level analysis technique for better segment truncation. From both theoretical and practical points of view, this research not only helps in increasing our knowledge of music structure but also facilitates in time-saving browsing and assessing of music.

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