On GMM Kalman predictive coding of LSFS for packet loss

Shaminda Subasingha, Manohar N. Murthi, Søren Vang Andersen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

Gaussian Mixture Model (GMM)-based Kalman predictive coders have been shown to perform better than baselineGMM Recursive Coders in predictive coding of Line Spectral Frequencies (LSFs) for both clean and packet loss conditions However, these stationary GMM Kalman predictive coders were not specifically designed for operation in packet loss conditions. In this paper, we demonstrate an approach to the the design of GMM-based predictive coding for packet loss channels. In particular, we show how a stationary GMM Kalman predictive coder can be modified to obtain a set of encoding and decoding modes, each with different Kalman gains. This approach leads to more robust performance of predictive coding of LSFs in packet loss conditions, as the coder mismatch between the encoder and decoder are minimized. Simulation results show that this Robust GMM Kalman predictive coder performs better than other baseline GMM predictive coders with no increase in complexity. To the best of our knowledge, no previous work has specifically examined the design of GMM predictive coders for packet loss conditions.

Original languageEnglish (US)
Title of host publication2009 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings, ICASSP 2009
Pages4105-4108
Number of pages4
DOIs
StatePublished - Sep 23 2009
Event2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009 - Taipei, Taiwan, Province of China
Duration: Apr 19 2009Apr 24 2009

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009
CountryTaiwan, Province of China
CityTaipei
Period4/19/094/24/09

Keywords

  • GMM
  • Kalman filtering
  • Speech coding
  • Vector quantization

ASJC Scopus subject areas

  • Signal Processing
  • Software
  • Electrical and Electronic Engineering

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  • Cite this

    Subasingha, S., Murthi, M. N., & Andersen, S. V. (2009). On GMM Kalman predictive coding of LSFS for packet loss. In 2009 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings, ICASSP 2009 (pp. 4105-4108). [4960531] (ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings). https://doi.org/10.1109/ICASSP.2009.4960531