Switched Conditional PDF-Based Split VQ Using Gaussian Mixture Model

Chatterjee, Saikat and Sreenivas, TV (2008) Switched Conditional PDF-Based Split VQ Using Gaussian Mixture Model. In: IEEE Signal Processing Letters, 15 . pp. 91-94.

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Abstract

In this letter, we develop switched conditional PDF-based split vector quantization (SCSVQ) method using the recently proposed conditional PDF-based split vector quantizer (CSVQ). The use of CSVQ allows us to alleviate the coding loss by exploiting the correlation between subvectors, in each switching region. Using the Gaussian mixture model (GMM)-based parametric framework, we also address the rate-distortion (R/D) performance optimality of the proposed SCSVQ method by allocating the bits optimally among the switching regions. For the wideband speech line spectrum frequency (LSF) parameter quantization, it is shown that the optimum parametric SCSVQ method provides nearly 2 bits/vector advantage over the recently proposed nonparametric switched split vector quantization (SSVQ) method.

Item Type:	Journal Article
Publication:	IEEE Signal Processing Letters
Publisher:	IEEE
Additional Information:	Copyright 2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Keywords:	Gaussian mixture model (GMM);line spectrum frequency (LSF) coding;vector quantization.
Department/Centre:	Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited:	24 Sep 2008 11:25
Last Modified:	19 Sep 2010 04:50
URI:	http://eprints.iisc.ac.in/id/eprint/15975

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