Du Li-min, Xie Ling-yun, Liu Bin. Embedded Implementation of HMM Speaker-Independent Continuous Speech Recognition System[J]. Journal of Electronics & Information Technology, 2005, 27(1): 60-63.
Citation:
Du Li-min, Xie Ling-yun, Liu Bin. Embedded Implementation of HMM Speaker-Independent Continuous Speech Recognition System[J]. Journal of Electronics & Information Technology, 2005, 27(1): 60-63.
Du Li-min, Xie Ling-yun, Liu Bin. Embedded Implementation of HMM Speaker-Independent Continuous Speech Recognition System[J]. Journal of Electronics & Information Technology, 2005, 27(1): 60-63.
Citation:
Du Li-min, Xie Ling-yun, Liu Bin. Embedded Implementation of HMM Speaker-Independent Continuous Speech Recognition System[J]. Journal of Electronics & Information Technology, 2005, 27(1): 60-63.
The embedded systems are gradually becoming the first choice of platforms which should be used for real-time speech recognition system. This paper discusses the computation complexity factors of HMM-based continuous speech recognition for embedded system. An optimized way integrating feature masking and pruning is presented to reduce the computation complexity and keep the recognition accuracy. The experiments for embedded system show that, comparing with the base-line system, the computation time is reduced from 100% to 27.91%, and the recognition accuracy is degraded only from 89.65% to 89.41%.
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