Math @ Duke
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Publications [#226621] of Paul L Bendich
Papers Accepted
- Christopher J Tralie and Paul Bendich, Cover Song Identification with Timbral Shape,
Proceedings of the 16th International Society for Music Information Retrieval
(2015),
pp. 38-44 [1507.05143]
(last updated on 2015/11/06)
Abstract: We introduce a novel low level feature for identifying cover songs which quantifies the relative changes
in the smoothed frequency spectrum of a song. Our key insight is that a sliding window representation
of a chunk of audio can be viewed as a time-ordered point cloud in high dimensions. For corresponding
chunks of audio between different versions of the same song, these point clouds are approximately rotated,
translated, and scaled copies of each other. If we treat MFCC embeddings as point clouds and cast the
problem as a relative shape sequence, we are able to correctly identify 42/80 cover songs in the “Covers
80” dataset. By contrast, all other work to date on cover songs exclusively relies on matching note
sequences from Chroma derived features.
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