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Aalborg Universitet On music genre classification via compressive sampling
| Content Provider | Semantic Scholar |
|---|---|
| Author | Šturm |
| Copyright Year | 2013 |
| Abstract | Recent work [1] combines low-level acoustic features and random projection (referred to as “compressed sensing” in [1]) 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 lowlevel 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. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://vbn.aau.dk/files/75520950/CSgenre20130312.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |