Index assignment for predictive wideband LSF quantization

Author

Ruoppila, Vesa T. ; Ragot, Stéphane

Author_Institution

Dept. of Electr. Eng., Sherbrooke Univ., Que., Canada

fYear

2000

fDate

2000

Firstpage

108

Lastpage

110

Abstract

In this paper we summarize some results derived earlier for the mean-square channel distortion of an autoregressive moving average (ARMA) vector quantizer with a maximum entropy encoder when the channel is assumed binary symmetric and memoryless. We discuss the required assumptions and their practical consequences in index assignment of ARMA vector quantizers. The discussion relates also to channel optimization of these quantizers. Furthermore, we compare noisy channel performance of memoryless, moving average, and autoregressive two-stage vector quantizers in line spectrum frequency quantization applied to wideband speech coding

Keywords

autoregressive moving average processes; entropy codes; linear predictive coding; maximum entropy methods; speech coding; vector quantisation; 25 to 7000 Hz; ARMA VQ; autoregressive moving average vector quantizer; binary symmetric channel; channel optimization; index assignment; line spectrum frequency quantization; maximum entropy encoder; mean-square channel distortion; memoryless channel; noisy channel performance; predictive wideband LSF quantization; two-stage vector quantizers; wideband speech coding; Autoregressive processes; Decoding; Entropy; Equations; Error probability; Frequency; Quantization; Resilience; Speech coding; Wideband;

fLanguage

English

Publisher

ieee

Conference_Titel

Speech Coding, 2000. Proceedings. 2000 IEEE Workshop on

Conference_Location

Delavan, WI

Print_ISBN

0-7803-6416-3

Type

conf

DOI

10.1109/SCFT.2000.878415

Filename

878415