Name
Abstract | ||
|---|---|---|
Categorization and retrieval to multimedia for audio is a significant problem because of new technology has developed very rapidly. Content retrieval techniques are vital in order to gather information from categorized record. In literature Zero Crossing Rate (ZCR), Root Mean Square (RMS), Spectral Flux (SF), Spectral Centroid (SC) and Spectral Roll off (SR) features are used. Support Vector Machine (SVM) classifier is used for audio content analysis. Root Mean Square is more effective classifier feature than other features. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/SIU.2013.6531339 | Signal Processing and Communications Applications Conference |
Keywords | Field | DocType |
audio signal processing,mean square error methods,speech synthesis,support vector machines,SVM classifier,audio content analysis,feature effectiveness analysis,multimedia categorization,multimedia retrieval,music categorization,retrieval techniques,root mean square,spectral centroid,spectral flux,spectral roll off,speech categorization,support vector machine,zero crossing rate,Audio Content Analysis,Forward Feature Selection Algorithm,Root Mean Square (RMS),Spectral Centroid (SC),Spectral Roll off (SR),Spectrum Flux (SF),Support Vector Machine (SVM),Zero Crossing Rate (ZCR) | Categorization,Spectral centroid,Pattern recognition,Computer science,Support vector machine,Speech recognition,Artificial intelligence,Root mean square,Audio signal processing,Classifier (linguistics),Zero-crossing rate,Spectral flux | Conference |
ISSN | ISBN | Citations |
2165-0608 | 978-1-4673-5561-2 | 0 |
PageRank | References | Authors |
0.34 | 2 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Esen Ozbayramoglu | 1 | 0 | 0.34 |
| Ahmet Cosar | 2 | 177 | 21.81 |
| Adnan Yazici | 3 | 649 | 56.29 |