Automatic analysis of the structure of a music piece aims to recover its sectional form: segmentation to musical parts, such as chorus or verse, and detecting repeated occurrences. A music signal is here described with features that are assumed to deliver information about its structure: mel-frequency cepstral coefficients, chroma, and rhythmogram. The features can be focused on different time scales of the signal. Two distance measures are presented for comparing musical sections: “stripes” for detecting repeated feature sequences, and “blocks” for detecting homogenous sections. The features and their time scales are evaluated in a systemindependent manner. Based on the obtained information, the features and distance measures are evaluated in an automatic structure analysis system with a large music database with manually annotated structures. The evaluations show that in a realistic situation, feature combinations perform better than individual features.

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