DocumentCode :
1056698
Title :
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
Link To Document :
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