Evaluation of time domain features for voiced/non-voiced classification of speech

Author

Ykhlef, F. ; Bendaouia, L.

Author_Institution

Syst. Archit. & Multimedia Div., CDTA, Algiers, Algeria

fYear

2012

fDate

18-21 Sept. 2012

Firstpage

1

Lastpage

4

Abstract

In this paper, we have performed an evaluation of several time domain features for voiced/non-voiced classification of speech signal. We have chosen in a seamless way three features: autocorrelation function (ACF), average magnitude difference function (AMDF) and weighted ACF (WACF) to form three different classifiers. Experimental results were conducted on TIMIT database in clean and noisy environments. The white noise extracted from the NOISEX92 database has been incorporated to validate the developed classifiers. We have established an overall ranking of these classifiers based on the average value of the percentage of classification accuracy (Pc).

Keywords

feature extraction; signal classification; speech processing; time-domain analysis; white noise; ACF; AMDF; NOISEX92 database; TIMIT database; WACF; autocorrelation function; average magnitude difference function; speech signal classification; time-domain feature evaluation; voiced-nonvoiced classification; weighted ACF; white noise extraction; Accuracy; Correlation; Databases; Feature extraction; Noise measurement; Speech; Speech processing;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals and Electronic Systems (ICSES), 2012 International Conference on

Conference_Location

Wroclaw

Print_ISBN

978-1-4673-1710-8

Electronic_ISBN

978-1-4673-1709-2

Type

conf

DOI

10.1109/ICSES.2012.6382213

Filename

6382213