ePrints@IIScePrints@IISc Home | About | Browse | Latest Additions | Advanced Search | Contact | Help

Reduced complexity two stage vector quantization

Chatterjee, Saikat and Sreenivas, TV (2009) Reduced complexity two stage vector quantization. In: Digital Signal Processing, 19 (3). pp. 476-490.

[img] PDF
fulltext.pdf - Published Version
Restricted to Registered users only

Download (611Kb) | Request a copy
Official URL: http://www.sciencedirect.com/science?_ob=ArticleUR...

Abstract

We address the issue of complexity for vector quantization (VQ) of wide-band speech LSF (line spectrum frequency) parameters. The recently proposed switched split VQ (SSVQ) method provides better rate-distortion (R/D) performance than the traditional split VQ (SVQ) method, even at the requirement of lower computational complexity. but at the expense of much higher memory. We develop the two stage SVQ (TsSVQ) method, by which we gain both the memory and computational advantages and still retain good R/D performance. The proposed TsSVQ method uses a full dimensional quantizer in its first stage for exploiting all the higher dimensional coding advantages and then, uses an SVQ method for quantizing the residual vector in the second stage so as to reduce the complexity. We also develop a transform domain residual coding method in this two stage architecture such that it further reduces the computational complexity. To design an effective residual codebook in the second stage, variance normalization of Voronoi regions is carried out which leads to the design of two new methods, referred to as normalized two stage SVQ (NTsSVQ) and normalized two stage transform domain SVQ (NTsTrSVQ). These two new methods have complimentary strengths and hence, they are combined in a switched VQ mode which leads to the further improvement in R/D performance, but retaining the low complexity requirement. We evaluate the performances of new methods for wide-band speech LSF parameter quantization and show their advantages over established SVQ and SSVQ methods.

Item Type: Journal Article
Additional Information: Copyright of this article belongs to Elsevier Science.
Keywords: Structured vector quantization; LSF parameter quantization; Weighted square Euclidean distance
Department/Centre: Division of Electrical Sciences > Electrical Communication Engineering
Date Deposited: 03 Jan 2010 10:52
Last Modified: 19 Sep 2010 05:32
URI: http://eprints.iisc.ernet.in/id/eprint/20431

Actions (login required)

View Item View Item