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Speech Communication
Volume 49, Issue 6, June 2007, Pages 490-500
 
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doi:10.1016/j.specom.2007.04.002    How to Cite or Link Using DOI (Opens New Window)
Copyright © 2007 Elsevier B.V. All rights reserved.

Predictive vector quantization of wideband LSF using narrowband LSF for bandwidth scalable codersstar, open

Hiroyuki EharaCorresponding Author Contact Information, a, E-mail The Corresponding Author, Toshiyuki Moriia and Koji Yoshidaa

aNext-Generation Mobile Communication Development Center, Matsushita Electric Industrial Co. Ltd. (Panasonic), 239-0847 Yokosuka, Japan

Received 20 February 2006; 
revised 1 February 2007; 
accepted 11 April 2007. 
Available online 18 April 2007.

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Abstract

For implementing a bandwidth-scalable coder, a wideband line spectral frequency (LSF) quantizer was developed. It works in combination with a narrowband LSF quantizer. A new predictive vector quantization was introduced to the wideband LSF quantizer. The predictive vector quantizer is based on the use of several predictive contributions, which include first-order auto regressive (AR) prediction and vector quantization (VQ) codebook mapping. One feature of the new predictive vector quantizer is exploitation of the correlation between wideband and narrowband LSFs quantized in the previous frame for estimating wideband LSF in the current frame. A 16-bit switched predictive three-stage vector quantizer was used to encode estimation residues. Results showed that introduction of the predictor brought about a performance improvement of 0.3 dB in spectral distortion. This paper describes procedures of designing the predictor and the three-stage codebook, as well as simulation results.

Keywords: Predictive vector quantization; LSF; LSP; Bandwidth scalability; Codebook mapping

Article Outline

1. Introduction
2. Bandwidth scalable LSF quantizer
2.1. Signal analysis
2.2. NB-LSF quantizer
2.3. Upsampling of NB-LSF
2.4. Switched predictive three-stage VQ
3. Predictive VQ
3.1. Preliminary experiment
3.2. Experimental results
4. VQ codebook mapping
4.1. Preliminary experiment
4.2. New PVQ algorithm
5. Training procedures
5.1. Codebook for mapping
5.2. Predictor coefficients
5.2.1. Initial coefficients
5.2.2. Update of predictor coefficients
5.3. Three-stage VQ codebook
5.3.1. Initial codebook
5.3.2. Update of codebook
6. Performance evaluation
7. Complexity
8. Conclusion
Appendix A. Upsampling of autocorrelation coefficients
References











Speech Communication
Volume 49, Issue 6, June 2007, Pages 490-500
 
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