NDLI: Estimation and vector quantization of noisy speech

Content Provider	IEEE Xplore Digital Library
Author	Gibson, J.D. Fischer, T.R. Koo, B.
Copyright Year	1988
Description	Author affiliation: Dept. of Electr. Eng., Texas A&M Univ., College Station, TX, USA (Gibson, J.D.; Fischer, T.R.; Koo, B.)
Abstract	The block and alphabet-constrained formulations are compared for the problem of vector quantization of noisy speech. In the optimum estimator/source-coder structures, a training mode vector quantizer due to Linde et al. (1980) is used as the source coder for the estimator outputs in all cases, and three block estimators and five alphabet-constrained estimators are examined. Objective and subjective performance results are obtained for all eight estimators used in conjunction with training mode vector quantizers at a rate of 1 bit/dimension, for dimensions 1,2,. . . ,8, and 2 bits/dimension, for dimensions 1,2,3, and 4, on five sentences, The results show the superiority of the alphabet-constrained approach, using the frame-adaptive Kalman filter, with improvements in output signal-to-noise ratio over the block approach of 20%.<>
Starting Page	541
Ending Page	544
File Size	357230
Page Count	4
File Format	PDF
ISSN	15206149
DOI	10.1109/ICASSP.1988.196640
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1988-04-11
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vector quantization Speech Decoding Block codes Gaussian noise Additive white noise Gaussian processes History Mean square error methods Kalman filters
Content Type	Text
Resource Type	Article

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