Audio Noise Classification using Bark scale features and K-NN Technique

Author

Eamdeelerd, Cherdchai ; Songwatana, Kraisin

Author_Institution

Dept. of Telecommun. Eng., King Mongkut´´s Inst. of Technol. Ladkrabang, Bangkok

fYear

2008

Firstpage

131

Lastpage

134

Abstract

This paper presents the audio noise classification using Bark scale features and K-NN technique. This paper uses audio noise signal from NOISEX-92 (12 types). We determine the transfer functions from linear predictive coding (LPC) coefficient of noise signal on Bark scale and use K-NN technique to classify them. The results will be used for optimization of speech recognition model in the presence of noise. The highest average accuracy for audio noise classification is obtained when K=3 and median over 5 consecutive frames.

Keywords

acoustic noise; audio coding; feature extraction; linear predictive coding; pattern classification; signal classification; speech coding; speech recognition; transfer functions; Bark scale feature; K-NN technique; audio noise classification; linear predictive coding; speech recognition model optimization; transfer function; Background noise; Electronic mail; Feature extraction; Linear predictive coding; Signal analysis; Speech analysis; Speech enhancement; Speech recognition; Transfer functions; Working environment noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Communications and Information Technologies, 2008. ISCIT 2008. International Symposium on

Conference_Location

Lao

Print_ISBN

978-1-4244-2335-4

Electronic_ISBN

978-1-4244-2336-1

Type

conf

DOI

10.1109/ISCIT.2008.4700168

Filename

4700168