A novel method for wavelet quantization of noisy speech

Author

Madhukumar, A.S. ; Premknmar, A.B. ; Abut, H.

Author_Institution

Centre for Wireless Commun., Singapore

Volume

1

fYear

1999

fDate

1999

Firstpage

142

Abstract

This paper proposes an architecture for low bit rate coding of noisy speech. The input noisy speech is decomposed into multiresolution signal components using the wavelet transform. An iterative Wiener filtering is used at each level of wavelet analysis to enhance speech. The system model that evolves during enhancement is processed further to get optimal parameters for the quantization. A multistage vector quantizer is used for compression of the decomposed speech. The enhanced speech is reconstructed at the receiving end by a VQ decoder and the necessary wavelet reconstruction network. The speech coding rate for the proposed architecture is estimated to be about 2.37 kbps

Keywords

AWGN; Wiener filters; autoregressive moving average processes; decoding; discrete wavelet transforms; filtering theory; iterative methods; signal reconstruction; signal resolution; speech coding; speech enhancement; vector quantisation; 2.37 kbit/s; ARMA modeling; AWGN; VQ decoder; additive white Gaussian noise; decomposed speech compression; discrete wavelet transforms; iterative Wiener filtering; low bit rate coding; multiresolution signal components; multistage vector quantizer; noisy speech; optimal parameters; speech coding; speech coding rate; speech enhancement; speech intelligibility; speech reconstruction; system model; wavelet analysis; wavelet quantization; wavelet reconstruction network; Bit rate; Decoding; Quantization; Signal resolution; Speech analysis; Speech coding; Speech enhancement; Wavelet analysis; Wavelet transforms; Wiener filter;

fLanguage

English

Publisher

ieee

Conference_Titel

TENCON 99. Proceedings of the IEEE Region 10 Conference

Conference_Location

Cheju Island

Print_ISBN

0-7803-5739-6

Type

conf

DOI

10.1109/TENCON.1999.818370

Filename

818370