On music genre classification via compressive sampling, 2013

Authors: Bob L. Sturm
Type: Conference paper
Conference: 2012 IEEE Conference on Multimedia & Expo
Titel: Proc. IEEE International Conference on Multimedia and Expo
Year: 2013

Abstract: 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.

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