Abstract
Many different short-time features, using time windows in the size of 10-30 ms, have been proposed for music
segmentation, retrieval and genre classification. However, often the available time frame of the music to make the
actual decision or comparison (the decision time horizon) is in the range of seconds instead of milliseconds. The
problem of making new features on the larger time scale from the short-time features (feature integration) has
only received little attention. This paper investigates different methods for feature integration and late information
fusion for music genre classification. A new feature integration
technique, the AR model, is proposed and seemingly outperforms the commonly used mean-variance features.
| Original language | English |
|---|---|
| Title of host publication | IEEE International Conference on Acoustics, Speech, and Signal Processing |
| Volume | V |
| Publication date | 2005 |
| Pages | 497-500 |
| Article number | 1416349 |
| ISBN (Print) | 0-7803-8874-7 |
| DOIs | |
| Publication status | Published - 2005 |
| Event | 2005 IEEE International Conference on Acoustics, Speech, and Signal Processing - Philadelphia, United States Duration: 18 Mar 2005 → 23 Mar 2005 Conference number: 30 http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=9711 |
Conference
| Conference | 2005 IEEE International Conference on Acoustics, Speech, and Signal Processing |
|---|---|
| Number | 30 |
| Country/Territory | United States |
| City | Philadelphia |
| Period | 18/03/2005 → 23/03/2005 |
| Internet address |
Bibliographical note
Copyright: 2005 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEEKeywords
- Audio classification
- early/late Information fusion,
- Feature Integration