This paper proposes a novel approach for rhythmic analysis of recorded percussion music based on information theory. Given an audio recording of a percussion music performance, the algorithm computes a lossy representation that captures much of its underlying regularity but tolerates some amount of distortion. Within a rate-distortion theory framework, the trade-off between rate and distortion allows for the extraction of some relevant information about the performance. Downbeat detection is addressed using lossy coding of an accentuation feature under rate-distortion criteria assuming the correct alignment produces the simplest explanation for the data. Experiments were conducted in order to assess the usefulness of the proposed approach when applied to a dataset of candombe drumming audio recordings. In particular, different performances were compared according to a measure of their overall complexity drawn from the operational rate-distortion curve, yielding results that roughly correspond to subjective judgment and correlate well with personal style and expertise.
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