Abstract
This paper presents a method to identify segment boundaries in music. The method is based on a hierarchical model; first a features is measured from the audio, then a measure of rhythm is calculated from the feature (the rhythmogram), the diagonal of a self-similarity matrix is calculated from the rhythmogram, and finally the segment boundaries are found on a smoothed novelty measure, calculated from the diagonal of the self-similarity matrix. All the steps of the model have been accompanied with an informal evaluation, and the final system is tested on a variety of rhythmic songs with good results. The paper introduces a new feature that is shown to work significantly better than previously used features, a robust rhythm model and a robust, relatively cheap method to identify structure from the novelty measure.
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Jensen, K. (2005). A Causal Rhythm Grouping. In: Wiil, U.K. (eds) Computer Music Modeling and Retrieval. CMMR 2004. Lecture Notes in Computer Science, vol 3310. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31807-1_6
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DOI: https://doi.org/10.1007/978-3-540-31807-1_6
Publisher Name: Springer, Berlin, Heidelberg
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