Split matrix quantization of LPC parameters

Author

Xydeas, Costas S. ; Papanastasiou, Charalampos

Author_Institution

Speech Process. Res. Lab., Manchester Univ., UK

Volume

7

Issue

2

fYear

1999

fDate

3/1/1999 12:00:00 AM

Firstpage

113

Lastpage

125

Abstract

This paper examines in detail the design issues and performance characteristics of linear predictive coding (LPC) split matrix quantization (SMQ). This efficient LPC quantization method which was proposed by Xydeas and Papanastasiou (1995) can be viewed as an extension of the conventional split vector quantization (SVQ) process. SMQ removes existing interframe/intraframe line spectral frequency (LSF) redundancy by applying VQ principles on trajectories of smoothly evolving, with time, LSF coefficients. Using a 20 ms LPC analysis frame size, “transparent” quantization is achieved at 900 b/s, whereas “high quality” LSF quantization is easily obtained at 650 b/s, Furthermore, the SMQ methodology offers valuable flexibility in the way quantization of LPC coefficients is performed and leads into several schemes of varying computational complexity/storage characteristics

Keywords

linear predictive coding; speech coding; vector quantisation; 650 bit/s; 900 bit/s; LPC parameters; LSF coefficients; SMQ; SVQ process; VQ principles; computational complexity; design; high quality LSF quantization; interframe/intraframe line spectral frequency redundancy; linear predictive coding; performance; split matrix quantization; split vector quantization; storage characteristics; transparent quantization; Bit rate; Computational complexity; Delay; Filters; Frequency; Linear predictive coding; Speech analysis; Speech coding; Speech synthesis; Vector quantization;

fLanguage

English

Journal_Title

Speech and Audio Processing, IEEE Transactions on

Publisher

ieee

ISSN

1063-6676

Type

jour

DOI

10.1109/89.748117

Filename

748117