Optimum switched split vector quantization of LSF parameters

Authors:
Saikat Chatterjee;T. V. Sreenivas
Affiliations:
Department of Electrical Communication Engineering, Indian Institute of Science, Bangalore 560 012, India;Department of Electrical Communication Engineering, Indian Institute of Science, Bangalore 560 012, India
Venue:
Signal Processing
Year:
2008

Citing 6
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Abstract

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 1bit/vector advantage over the non-parametric SSVQ method.