Estimation and vector quantization of noisy speech

Author

Gibson, Jerry D. ; Fischer, Thomas R. ; Koo, Boneung

Author_Institution

Dept. of Electr. Eng., Texas A&M Univ., College Station, TX, USA

fYear

1988

fDate

11-14 Apr 1988

Firstpage

541

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%

Keywords

Kalman filters; analogue-digital conversion; encoding; speech analysis and processing; ADC; alphabet-constrained estimators; alphabet-constrained formulations; block coding; block estimators; frame-adaptive Kalman filter; minimum mean-square error encoding; noisy speech; output signal-to-noise ratio; source coder; speech analysis; speech processing; training mode vector quantizer; vector quantization; Additive white noise; Block codes; Decoding; Gaussian noise; Gaussian processes; History; Kalman filters; Mean square error methods; Speech; Vector quantization;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1988. ICASSP-88., 1988 International Conference on

Conference_Location

New York, NY

ISSN

1520-6149

Type

conf

DOI

10.1109/ICASSP.1988.196640

Filename

196640