Error Recovery: Channel Coding and Packetization

  • Bengt J. Borgström
  • Alexis Bernard
  • Abeer Alwan
Part of the Advances in Pattern Recognition book series (ACVPR)

Distributed Speech Recognition (DSR) systems rely on efficient transmission of speech information from distributed clients to a centralized server. Wireless or network communication channels within DSR systems are typically noisy and bursty. Thus, DSR systems must utilize efficient Error Recovery (ER) schemes during transmission of speech information. Some ER strategies, referred to as forward error control (FEC), aim to create redundancy in the source coded bitstream to overcome the effect of channel errors, while others are designed to create spread or delay in the feature stream in order to overcome the effect of bursty channel errors. Furthermore, ER strategies may be designed as a combination of the previously described techniques. This chapter presents an array of error recovery techniques for remote speech recognition applications.

This chapter is organized as follows. First, channel characterization and modeling are discussed. Next, media-specific FEC is presented for packet erasure applications, followed by a discussion on media-independent FEC techniques for bit error applications, including general linear block codes, cyclic codes, and convolutional codes. The application of unequal error protection (UEP) strategies utilizing combinations of the aforementioned FEC methods is also presented. Finally, frame-based interleaving is discussed as an alternative to overcoming the effect of bursty channel erasures. The chapter concludes with examples of modern standards for channel coding strategies for distributed speech recognition (DSR).


Channel Code Cyclic Code Convolutional Code Error Recovery Unequal Error Protection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Bai, H., and Atiquzzaman, M. (2003). Error Modeling Schemes for Fading Channels in Wire-less Communications: A Survey. IEEE Communications Surveys and Tutorials, Fourth Quarter, vol. 5, no. 2, pp. 2-9.CrossRefGoogle Scholar
  2. Bernard, A., and Alwan, A. (2001). Joint Channel Decoding- Viterbi Recognition for Wireless Applications. Proceedings of Europspeech, vol. 3, pp. 2703-2706.Google Scholar
  3. Bernard, A., and Alwan, A. (2002a). Low-Bitrate Distributed Speech Recognition for Packet-Based and Wireless Communication. IEEE Transactions on Speech and Audio Processing, vol. 10, no. 8, pp. 570-579.CrossRefGoogle Scholar
  4. Bernard, A., Liu, X., Wesel, R., and Alwan, A. (2002b). Speech Transmission Using Rate-Compatible Trellis Codes and Embedded Source Coding. IEEE Transactions on Commu-nications, vol. 50, no. 2, pp. 309-320.CrossRefGoogle Scholar
  5. Bernard, A. (2002). Source and Channel Coding for Speech Transmission and Remote Speech Recognition, PhD Thesis, University of California, Los Angeles.Google Scholar
  6. Blahut, R.E. (2004). Algebraic Codes for Data Transmission. Cambridge University Press, Cambridge, UK.Google Scholar
  7. Bolot, J.-C. (2003). End-to-End Packet Delay and Loss Behavior in the Internet. ACM Sig-comm, pp. 289-298.Google Scholar
  8. Boulis, C., Ostendorf, M., Riskin, E. A., and Otterson, S. (2002). Graceful Degradation of Speech Recognition Performance Over Packet-Erasure Networks. IEEE Transactions on Speech and Audio Processing. vol. 10, no. 8, pp. 580-590.CrossRefGoogle Scholar
  9. Elliot, E. (1963). Estimates of Error Rates for Codes on Bursty Noise Channels. Bell Systems Technical Journal, vol. 42, no. 9.Google Scholar
  10. ETSI EN 300 909 v7.3.1 (1998). Digital Cellular Telecommunications System(Phase 2+)(GSM); Channel Coding.Google Scholar
  11. ETSI ES 201 108 v1.1.2 (2000). Distributed Speech Recognition; Front-end Feature Extrac-tion Algorithm; Compression Algorithms.Google Scholar
  12. Han, K.J., Srinivasamurthy, N., and Narayanan, S. (2004). Robust Speech Recognition over Packet Networks: An Overview. Proceedings of ICSLP, vol. 3, pp. 1791-1794.Google Scholar
  13. Hirsch, H.G., and Pearce, D. (2000). The AURORA Experimental Framework for the Per-formance Evaluation of Speech Recognition Systems under Noisy Condition. In Proceed-ings of ISCA ITRW ASR 2000.Google Scholar
  14. James, A.B., and Milner, B.P. (2004). An Analysis of Interleavers for Robust Speech Recogni-tion in Burst-Like Packet Loss. In Proceedings of ICASSP, vol. 1, pp. 853-856.Google Scholar
  15. Jiao, C., Schwiebert, L., and Xu, B. (2002). On Modeling the Packet Error Statistics in Bursty Channels. IEEE LCN, pp. 534-538.Google Scholar
  16. Leon-Garcia, A. (2007). Probability and Random Processes for Electrical Engineers. Prentice-Hall.Google Scholar
  17. Peinado, A.M., Gomez, A.M., Sanchez, V., Perez-Cordoba, J.L., and Rubio, A.J. (2005a). Packet Loss Concealment Based on VQ Replicas and MMSE Estimation Applied to Dis-tributed Speech Recognition. Proceedings of ICASSP. vol. 1, pp. 329-330.Google Scholar
  18. Peindo, A.M., Sanchez, V., Perez-Cordoba, J.L., and Rubio, A.J. (2005b). Efficient MMSE-Based Channel Error Mitigation Techniques. Application to Distributed Speech Recogni-tion Over Wireless Channels. IEEE Transactions on Wireless Communications, vol. 4, no. 1, pp.14-19.CrossRefGoogle Scholar
  19. Peindo, A.M., and Segura, J.C. (2006). Speech Recognition Over Digital Channels. Wiley, New York, West Sussex, England.CrossRefGoogle Scholar
  20. Sklar, B. (1997). Rayleigh Fading Channels in Mobile Digital Communication Systems Part 1: Characterization. IEEE Communications Magazine, pp. 90-100.Google Scholar
  21. Tan, Z.-H., Dalsgaard, P., and Lindberg, B. (2005). Automatic Speech Recognition over Error-Prone Wireless Networks. Speech Communication, vol. 47, pp. 220-242.CrossRefGoogle Scholar
  22. Weerackody, V., Reichl, W., and Potamianos, A. (2002). An Error-Protected Speech Recogni-tion System for Wireless Communications. IEEE Transactions on Wireless Communica-tions, vol. 1, no. 2, pp. 282-291.CrossRefGoogle Scholar
  23. Viterbi, A. (1971). Convolutional Codes and Their Performance in Communication Systems. IEEE Transactions on Communications, vol. 19, no. 5, part 1, pp. 751-772.CrossRefMathSciNetGoogle Scholar
  24. Wesel, R.D. (2003). Convolutional Codes, from Encyclopedia of Telecommunications. Wiley, New York.Google Scholar
  25. Young, S., Kershaw, D., Odell, J., Ollason, D., Valtchev, V., and Woodland, P. (2000). The HTK Book. Microsoft Corporation.Google Scholar

Copyright information

© Springer-Verlag London Limited 2008

Authors and Affiliations

  • Bengt J. Borgström
    • 1
  • Alexis Bernard
    • 1
  • Abeer Alwan
    • 1
  1. 1.Department of Electrical EngineeringUniversity of California, Los AngelesLos AngelesUSA

Personalised recommendations