Comparison of Nonuniform Optimal Quantizer Designs for Speech Coding With Adaptive Critics and Particle Swarm

Author

Venayagamoorthy, Ganesh Kumar ; Zha, Wenwei

Author_Institution

Dept. of Electr. & Comput. Eng., Missouri Univ., Rolla, MO

Volume

43

Issue

1

fYear

2007

Firstpage

238

Lastpage

244

Abstract

This paper presents the design of a companding nonuniform optimal scalar quantizer for speech coding. The quantizer is designed using two neural networks to perform the nonlinear transformation. These neural networks are used in the front and back ends of a uniform quantizer. Two approaches are presented in this paper namely adaptive critic designs and particle swarm optimization, aiming to maximize the signal-to-noise ratio. The comparison of these optimal quantizer designs over a bit-rate range of 3-6 is presented. The perceptual quality of the coding is evaluated by the International Telecommunication Union´s Perceptual Evaluation of Speech Quality standard

Keywords

neural nets; particle swarm optimisation; quantisation (signal); speech coding; International Telecommunication Union; Perceptual Evaluation of Speech Quality Standard; adaptive critics; neural networks; nonlinear transformation; nonuniform optimal scalar quantizer designs; particle swarm optimization; signal-to-noise ratio; speech coding; Bit rate; Neural networks; Particle swarm optimization; Quantization; Reactive power; Signal design; Signal to noise ratio; Speech analysis; Speech coding; Telecommunication standards; Adaptive critic designs (ACDs); neural networks; particle swarm optimization (PSO); perceptual evaluation of speech quality (PESQ); quantization; speech coding;

fLanguage

English

Journal_Title

Industry Applications, IEEE Transactions on

Publisher

ieee

ISSN

0093-9994

Type

jour

DOI

10.1109/TIA.2006.885897

Filename

4077216