Effectiveness Analysis of Features Used for Categorization of Music and Speech

Date

2013-01-01

Author

Oezbayramoglu, Esen
Coşar, Ahmet
Yazıcı, Adnan

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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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.

URI

https://hdl.handle.net/11511/117815

DOI

https://doi.org/10.1109/siu.2013.6531339

Conference Name

21st Signal Processing and Communications Applications Conference (SIU)

Collections

Department of Computer Engineering, Conference / Seminar

Citation Formats

E. Oezbayramoglu, A. Coşar, and A. Yazıcı, “Effectiveness Analysis of Features Used for Categorization of Music and Speech,” presented at the 21st Signal Processing and Communications Applications Conference (SIU), CYPRUS, 2013, Accessed: 00, 2025. [Online]. Available: https://hdl.handle.net/11511/117815.