Projects per year
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.
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 language | English |
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Journal | International Conference on Multimedia and Expo |
Publication status | Published - 2013 |
Event | 2012 IEEE Conference on Multimedia & Expo - San Jose, United States Duration: 15 Jul 2013 → 19 Jul 2013 |
Conference
Conference | 2012 IEEE Conference on Multimedia & Expo |
---|---|
Country/Territory | United States |
City | San Jose |
Period | 15/07/2013 → 19/07/2013 |
Fingerprint
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Greedy Sparse Approximation and the Automatic Description of Audio and Music Data
Sturm, B. L.
Technology and Production Independent Postdoc Center for Independent Research
01/01/2012 → …
Project: Research
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CoSound
Christensen, M. G., Tan, Z., Jensen, S. H. & Sturm, B. L.
01/01/2012 → 31/12/2015
Project: Research