DOI: 10.1007/978-3-642-11674-2_16
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Marcus T. Pearce, Daniel Müllensiefen, Geraint A. Wiggins

Abstract: We introduce the MIR task of segmenting melodies into phrases, summarise the musicological and psychological background to the task and review existing computational methods before presenting a new model, IDyOM, for melodic segmentation based on statistical learning and information-dynamic analysis. The performance of the model is compared to several existing algorithms in predicting the annotated phrase boundaries in a large corpus of folk music. The results indicate that four algorithms produce acceptable re…

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