Effectiveness analysis of features used for categorization of music and speech

Author

Ozbayramoglu, E. ; Cosar, A. ; Yazici, Adnan

Author_Institution

Bilgisayar Muhendisligi Bolumu, Orta Dogu Teknik Univ., Ankara, Turkey

fYear

2013

fDate

24-26 April 2013

Firstpage

1

Lastpage

4

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.

Keywords

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; Abstracts; MONOS devices; Root mean square; Silicon; Speech; Speech processing; Support vector machines; 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);

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing and Communications Applications Conference (SIU), 2013 21st

Conference_Location

Haspolat

Print_ISBN

978-1-4673-5562-9

Electronic_ISBN

978-1-4673-5561-2

Type

conf

DOI

10.1109/SIU.2013.6531339

Filename

6531339