Evaluating the effect of voice activity detection in isolated Yoruba word recognition system

Author

Aibinu, A.M. ; Salami, M.J.E. ; Najeeb, A.R. ; Azeez, J.F. ; Rajin, S.M.A.K.

Author_Institution

Mechatron. Dept., Int. Islamic Univ., Kuala Lumpur, Malaysia

fYear

2011

fDate

17-19 May 2011

Firstpage

1

Lastpage

5

Abstract

This paper discusses and evaluates the effect of voice Activity Detection (VAD) in an isolated Yoruba word recognition system (IYWRS). The word database used in this paper are collected from 22 speakers by repeating the numbers 1 to 9 three times each. A hybrid configuration of Mel-Frequency Cepstral coefficient (MFCC) and Linear Predictive Coding (LPC) have been used to extract the features of the speech samples. Artificial Neural Network algorithms are then used to classify these features. An overall accuracy of about 60% has been achieved from the two proposed feature extraction methods.

Keywords

feature extraction; linear predictive coding; neural nets; speech recognition; artificial neural network algorithm; feature extraction; hybrid configuration; isolated Yoruba word recognition system; linear predictive coding; mel-frequency cepstral coefficient; speech sample; voice activity detection; word database; Accuracy; Artificial neural networks; Feature extraction; Mel frequency cepstral coefficient; Speech; Speech recognition; Training;

fLanguage

English

Publisher

ieee

Conference_Titel

Mechatronics (ICOM), 2011 4th International Conference On

Conference_Location

Kuala Lumpur

Print_ISBN

978-1-61284-435-0

Type

conf

DOI

10.1109/ICOM.2011.5937134

Filename

5937134