Name
Title | ||
|---|---|---|
A learning approach to hierarchical feature selection and aggregation for audio classification |
Abstract | ||
|---|---|---|
Audio classification typically involves feeding a fixed set of low-level features to a machine learning method, then performing feature aggregation before or after learning. Instead, we jointly learn a selection and hierarchical temporal aggregation of features, achieving significant performance gains. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1016/j.patrec.2009.12.036 | Pattern Recognition Letters |
Keywords | Field | DocType |
feature aggregation,audio classification,hierarchical feature selection,feature selection,fixed set,temporal modeling,low-level feature,significant performance gain,hierarchical temporal aggregation,machine learning | Signal processing,Pattern recognition,Feature selection,Computer science,Feature extraction,Speech recognition,Artificial intelligence,Temporal modeling,Audio signal processing,Feature aggregation,Feature learning | Journal |
Volume | Issue | ISSN |
31 | 12 | Pattern Recognition Letters |
Citations | PageRank | References |
11 | 0.56 | 21 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Paul Ruvolo | 1 | 486 | 29.52 |
| Ian Fasel | 2 | 431 | 31.58 |
| Javier R. Movellan | 3 | 1853 | 150.44 |