On music genre classification via compressive sampling

Bob L. Sturm

Research output: Contribution to journalConference article in JournalResearchpeer-review

15 Citations (Scopus)
975 Downloads (Pure)


Recent work \cite{Chang2010} combines low-level acoustic features
and random projection (referred to as ``compressed sensing'' in \cite{Chang2010})
to create a music genre classification system showing
an accuracy among the highest reported
for a benchmark dataset.
This not only contradicts previous findings
that suggest low-level features are inadequate for
addressing high-level musical problems,
but also that a random projection of features
can improve classification.
We reproduce this work and resolve these contradictions.
Original languageEnglish
JournalInternational Conference on Multimedia and Expo
Publication statusPublished - 2013
Event2012 IEEE Conference on Multimedia & Expo - San Jose, United States
Duration: 15 Jul 201319 Jul 2013


Conference2012 IEEE Conference on Multimedia & Expo
Country/TerritoryUnited States
CitySan Jose


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