Projekter pr. år
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.
| Originalsprog | Engelsk |
|---|---|
| Tidsskrift | International Conference on Multimedia and Expo |
| Status | Udgivet - 2013 |
| Begivenhed | 2012 IEEE Conference on Multimedia & Expo - San Jose, USA Varighed: 15 jul. 2013 → 19 jul. 2013 |
Konference
| Konference | 2012 IEEE Conference on Multimedia & Expo |
|---|---|
| Land/Område | USA |
| By | San Jose |
| Periode | 15/07/2013 → 19/07/2013 |
Fingeraftryk
Dyk ned i forskningsemnerne om 'On music genre classification via compressive sampling'. Sammen danner de et unikt fingeraftryk.-
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 → …
Projekter: Projekt › Forskning
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CoSound
Christensen, M. G., Tan, Z., Jensen, S. H. & Sturm, B. L.
01/01/2012 → 31/12/2015
Projekter: Projekt › Forskning