Memory-enhanced MMSE-based channel error mitigation for distributed speech recognition

Cheng Lung Lee*, Wen-Whei Chang

*Corresponding author for this work

Research output: Contribution to conferencePaper

Abstract

A new approach to sequence minimum mean-squared error (SMMSE) decoding for vector quantization over channels with memory is presented. The decoder is based on the Gilbert channel model that allows the exploitation of intra-vector correlation of bit error sequences. We apply the memory-enhanced SMMSE decoding algorithm to channel error mitigation in distributed speech recognition. Experiments on Mandarin digit string recognition task indicate that with the aid of Gilbert channel characterization, the proposed scheme obtains better performance than the ETSI mitigation algorithm under GSM channel conditions.

Original languageEnglish
Pages3137-3140
Number of pages4
StatePublished - 1 Dec 2005
Event9th European Conference on Speech Communication and Technology - Lisbon, Portugal
Duration: 4 Sep 20058 Sep 2005

Conference

Conference9th European Conference on Speech Communication and Technology
CountryPortugal
CityLisbon
Period4/09/058/09/05

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  • Cite this

    Lee, C. L., & Chang, W-W. (2005). Memory-enhanced MMSE-based channel error mitigation for distributed speech recognition. 3137-3140. Paper presented at 9th European Conference on Speech Communication and Technology, Lisbon, Portugal.