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Quantitative Analysis of a Common Audio Similarity Measure

Jesper Hojvang Jensen; Mads Gaesboll Christensen; Daniel P. W. Ellis; Soren Holdt Jensen

Title:
Quantitative Analysis of a Common Audio Similarity Measure
Author(s):
Jensen, Jesper Hojvang
Christensen, Mads Gaesboll
Ellis, Daniel P. W.
Jensen, Soren Holdt
Date:
Type:
Articles
Department:
Electrical Engineering
Volume:
17
Permanent URL:
Book/Journal Title:
IEEE Transactions on Audio, Speech, and Language Processing
Abstract:
For music information retrieval tasks, a nearest neighbor classifier using the Kullback-Leibler divergence between Gaussian mixture models of songs' melfrequency cepstral coefficients is commonly used to match songs by timbre. In this paper, we analyze this distance measure analytically and experimentally by the use of synthesized MIDI files, and we find that it is highly sensitive to different instrument realizations. Despite the lack of theoretical foundation, it handles the multipitch case quite well when all pitches originate from the same instrument, but it has some weaknesses when different instruments play simultaneously. As a proof of concept, we demonstrate that a source separation frontend can improve performance. Furthermore, we have evaluated the robustness to changes in key, sample rate, and bitrate.
Subject(s):
Electrical engineering
Acoustics
Publisher DOI:
http://dx.doi.org/10.1109/TASL.2008.2012314
Item views:
147
Metadata:
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