Open Access

Multiple-Description Multistage Vector Quantization

EURASIP Journal on Audio, Speech, and Music Processing20072007:067146

DOI: 10.1155/2007/67146

Received: 19 May 2007

Accepted: 31 October 2007

Published: 3 December 2007

Abstract

Multistage vector quantization (MSVQ) is a technique for low complexity implementation of high-dimensional quantizers, which has found applications within speech, audio, and image coding. In this paper, a multiple-description MSVQ (MD-MSVQ) targeted for communication over packet-loss channels is proposed and investigated. An MD-MSVQ can be viewed as a generalization of a previously reported interleaving-based transmission scheme for multistage quantizers. An algorithm for optimizing the codebooks of an MD-MSVQ for a given packet-loss probability is suggested, and a practical example involving quantization of speech line spectral frequency (LSF) vectors is presented to demonstrate the potential advantage of MD-MSVQ over interleaving-based MSVQ as well as traditional MSVQ based on error concealment at the receiver.

[12345678910111213]

Authors’ Affiliations

(1)
Department of Electrical and Computer Engineering, University of Manitoba

References

  1. Goyal VK: Multiple description coding: compression meets the network. IEEE Signal Processing Magazine 2001,18(5):74-93. 10.1109/79.952806View ArticleGoogle Scholar
  2. Vaishampayan VA: Design of multiple description scalar quantizers. IEEE Transactions on Information Theory 1993,39(3):821-834. 10.1109/18.256491View ArticleMATHGoogle Scholar
  3. Gersho A, Gray RM: Vector Quantization and Signal Compression. Kluwer Academic, Boston, Mass, USA; 1992.View ArticleMATHGoogle Scholar
  4. Juang B-H, Gray AH Jr.: Multiple stage vector quantization for speech coding. Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '82), May 1982, Paris, France 7: 597-600.View ArticleGoogle Scholar
  5. Krishnan V, Anderson DV, Truong KK: Optimal multistage vector quantization of LPC parameters over noisy channels. IEEE Transactions on Speech and Audio Processing 2004,12(1):1-8. 10.1109/TSA.2003.819945View ArticleGoogle Scholar
  6. Chan W-Y, Gersho : High fidelity audio transform coding with vector quantization. Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '90), 1990, Albuquerque, NM, USA 2: 1109-1112.Google Scholar
  7. Kossentini S, Smith MTJ, Barnes CF: Image coding using entropy-constrained residual vector quantization. IEEE Transactions on Image Processing 1995,4(10):1349-1357. 10.1109/83.465100View ArticleGoogle Scholar
  8. Khalil H, Rose K: Multistage vector quantizer optimization for packet networks. IEEE Transactions on Signal Processing 2003,51(7):1870-1879. 10.1109/TSP.2003.812731View ArticleGoogle Scholar
  9. LeBlanc WP, Bhattacharya B, Mahmoud SA, Cuperman V: Efficient search and design procedures for robust multi-stage VQ of LPC parameters for 4 kb/s speech coding. IEEE Transactions on Speech and Audio Processing 1993,1(4):373-385. 10.1109/89.242483View ArticleGoogle Scholar
  10. Supplee LM, Cohn RP, Collura JS, McCree AV: MELP: the new federal standard at 2400 bps. Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97), 1997 2: 1591-1594.Google Scholar
  11. National Institute of Standards & Technology (NIST) : The DARPA TIMIT Acoustic Continuous Speech Corpus (CD-ROM). NIST, 1990Google Scholar
  12. Paliwal KK, Atal BS: Efficient vector quantization of LPC parameters at 24 bits/frame. IEEE Transactions on Speech and Audio Processing 1993,1(1):3-14. 10.1109/89.221363View ArticleGoogle Scholar
  13. 3rd Generation Partnership Project (3GPP) : Adaptive multi-rate (AMR) speech codec; error concealment of lost frames. In Technical Specification 3G TS 26.091. 3GPP, Valbonne, France; 1999. http://www.3gpp.orgGoogle Scholar

Copyright

© Pradeepa Yahampath. 2007

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.