NDLI: Signal bias removal for robust telephone based speech recognition in adverse environments

Content Provider	IEEE Xplore Digital Library
Author	Rahim, M.G. Biing-Hwang Juang
Copyright Year	1994
Description	Author affiliation: AT&T Bell Labs., Murray Hill, NJ, USA (Rahim, M.G.; Biing-Hwang Juang)
Abstract	A speech signal transmitted through a telephone channel often encounters variable conditions which significantly deteriorate the performance of state-of-the-art HMM-based speech recognition systems. Undesirable components due to ambient noise and channel interference, as well as different sound pick-up equipments, render the recognizer unsuitable for real-world applications. This paper presents a signal bias removal method based on the maximum likelihood estimation for the minimization of these undesirable effects. The proposed method, integrated into a discrete density HMM, is applied to telephone speech recognition where the contamination due to ambient noise and channel distortion are assumed to be unknown. Experimental results are presented for speaker-independent connected digit recognition which demonstrate a reduction in the word error rate by up to 40%.<>
File Size	340676
File Format	PDF
ISBN	0780317750
ISSN	15206149
DOI	10.1109/ICASSP.1994.389260
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1994-04-19
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Telephony Speech recognition Acoustic noise Noise robustness Interference Maximum likelihood estimation Minimization methods Hidden Markov models Contamination Error analysis
Content Type	Text
Resource Type	Article

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