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Optimum switched split vector quantization of LSF parameters

We address the issue of rate–distortion (R/D) performance optimality of the recently proposed switched split vector quantization (SSVQ) method. The distribution of the source is modeled using Gaussian mixture density and thus, the non-parametric SSVQ is analyzed in a parametric model based framework...

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Published in:Signal processing 2008-06, Vol.88 (6), p.1528-1538
Main Authors: Chatterjee, Saikat, Sreenivas, T.V.
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cited_by cdi_FETCH-LOGICAL-c373t-3779f69c5f1838fffe01b3d1f492de71936de5446f536ce605b3395892b2f5e13
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description We address the issue of rate–distortion (R/D) performance optimality of the recently proposed switched split vector quantization (SSVQ) method. The distribution of the source is modeled using Gaussian mixture density and thus, the non-parametric SSVQ is analyzed in a parametric model based framework for achieving optimum R/D performance. Using high rate quantization theory, we derive the optimum bit allocation formulae for the intra-cluster split vector quantizer (SVQ) and the inter-cluster switching. For the wide-band speech line spectrum frequency (LSF) parameter quantization, it is shown that the Gaussian mixture model (GMM) based optimum parametric SSVQ method provides 1 bit/vector advantage over the non-parametric SSVQ method.
doi_str_mv 10.1016/j.sigpro.2008.01.001
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subjects Applied sciences
Coding, codes
Exact sciences and technology
Gaussian mixture model
Information, signal and communications theory
LPC quantization
Sampling, quantization
Signal and communications theory
Signal processing
speech coding
Speech processing
SRA - ICT
SRA - Informations- och kommunikationsteknik
Telecommunications and information theory
Vector quantization
title Optimum switched split vector quantization of LSF parameters
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