Academic Commons


Cross-Correlation of Beat-Synchronous Representations for Music Similarity

Ellis, Daniel P. W.; Cotton, Courtenay Valentine; Mandel, Michael I.

Systems to predict human judgments of music similarity directly from the audio have generally been based on the global statistics of spectral feature vectors i.e. collapsing any large-scale temporal structure in the data. Based on our work in identifying alternative ("cover") versions of pieces, we investigate using direct correlation of beat-synchronous representations of music audio to find segments that are similar not only in feature statistics, but in the relative positioning of those features in tempo-normalized time. Given a large enough search database, good matches by this metric should have very high perceived similarity to query items. We evaluate our system through a listening test in which subjects rated system-generated matches as similar or not similar, and compared results to a more conventional timbral and rhythmic similarity baseline, and to random selections.


Also Published In

2008 IEEE International Conference on Acoustics, Speech, and Signal Processing: ICASSP '08: Proceedings: March 30-April 4, 2008 Caesars Palace Las Vegas, Nevada, U.S.A.

More About This Work

Academic Units
Electrical Engineering
Published Here
June 27, 2012
Academic Commons provides global access to research and scholarship produced at Columbia University, Barnard College, Teachers College, Union Theological Seminary and Jewish Theological Seminary. Academic Commons is managed by the Columbia University Libraries.