Title :
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
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;
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
DOI :
10.1109/ISCIT.2008.4700168
