Speech compression using ARMA model and wavelet transform

Author

Park, Sung-won

Author_Institution

Dept. of Electr. Eng. & Comput. Sci., Texas A&M Univ., Kingsville, TX, USA

fYear

1994

fDate

19-22 Apr 1994

Abstract

In LPC (linear predictive coding) vocoding, because of the insufficiency of the all-pole model, reconstructed speech is often crude unless much information about the residual error is also transmitted. To improve the quality, ARMA parameters of each bandpass filter output of a filter bank are extracted and transmitted in this paper. A general idea of the wavelet transform is utilized for design of the filter bank. Both the ARMA model and the wavelet transform are well known. But a combination of these technique has not been exploited in speech coding. This paper may lead to the new way for the very low-rate speech coding

Keywords

autoregressive moving average processes; band-pass filters; data compression; filtering theory; linear predictive coding; speech coding; speech intelligibility; wavelet transforms; ARMA model; ARMA parameters; LPC; bandpass filter output; filter bank; linear predictive coding; reconstructed speech; residual error; speech coding; speech compression; speech quality; vocoding; wavelet transform; Computational complexity; Filter bank; Iterative algorithms; Least squares approximation; Linear predictive coding; Parameter estimation; Poles and zeros; Pulse modulation; Speech coding; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1994. ICASSP-94., 1994 IEEE International Conference on

Conference_Location

Adelaide, SA

ISSN

1520-6149

Print_ISBN

0-7803-1775-0

Type

conf

DOI

10.1109/ICASSP.1994.389318

Filename

389318