Noise immune speech recognition system

Author

Gadallah, Mohmoud ; Soleit, Elsayed ; Mahran, Ashraf

Author_Institution

Mil. Tech. Coll., Cairo, Egypt

fYear

1999

fDate

23-25 Feb 1999

Abstract

This paper investigates the performance of an isolated word recognition (IWR) system in a noisy environment. Two approaches have been demonstrated to overcome the effect of the noise on the recognition accuracy. These approaches are, using noise immune features and reference model contamination. The performance is evaluated in a noisy environment at different signal-to-noise ratios (SNR), with different feature extraction techniques including linear predictive coding (LPC), cepstrum analysis, weighted cepstrum analysis, and perceptual linear predictive coding (PLP). The performance of these features is compared based on the recognition accuracy. The results have shown that the PLP features exhibits the best noise immunity and recognition accuracy among the studied features

Keywords

cepstral analysis; feature extraction; linear predictive coding; noise; speech coding; speech recognition; LPC; SNR; cepstrum analysis; feature extraction techniques; isolated word recognition; linear predictive coding; noise immune features; noise immune speech recognition system; noisy environment; perceptual linear predictive coding; performance evaluation; recognition accuracy; reference model contamination; signal-to-noise ratio; weighted cepstrum analysis; Cepstral analysis; Cepstrum; Contamination; Feature extraction; Linear predictive coding; Performance analysis; Signal analysis; Signal to noise ratio; Speech recognition; Working environment noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Radio Science Conference, 1999. NRSC '99. Proceedings of the Sixteenth National

Conference_Location

Cairo

Print_ISBN

977-5031-62-1

Type

conf

DOI

10.1109/NRSC.1999.760905

Filename

760905