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.
|Number of pages||4|
|State||Published - 1 Dec 2005|
|Event||9th European Conference on Speech Communication and Technology - Lisbon, Portugal|
Duration: 4 Sep 2005 → 8 Sep 2005
|Conference||9th European Conference on Speech Communication and Technology|
|Period||4/09/05 → 8/09/05|