Design and optimization of a low resource speech recognition system

ZHANG Pengyuan; JI Zhe; HOU Wei; JIN Xin; HAN Weisheng

doi:10.16511/j.cnki.qhdxxb.2017.22.006

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Journal of Tsinghua University(Science and Technology) ›› 2017, Vol. 57 ›› Issue (2) : 147-152. DOI: 10.16511/j.cnki.qhdxxb.2017.22.006

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Design and optimization of a low resource speech recognition system

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Abstract

Wearable devices and smart home systems need speech recognition engines with few resources and high rejection rates. Traditional methods cannot provide such systems. This paper presents algorithms for decoding and rejection for a low source speech recognition system. The decoding improves the rejection rate up to 64.8% by changing the filler reentry while the memory is only increased 8.5 kB compared with the baseline system. The rejection algorithm computes a background probability which is compared to similar probabilities calculated in advance online decoding. The system gives a rejection rate of 93.8% with little loss in the recognition rate. The memory and computational speed are also optimized.

Key words

speech recognition / low resource / confidence measure

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ZHANG Pengyuan, JI Zhe, HOU Wei, JIN Xin, HAN Weisheng. Design and optimization of a low resource speech recognition system[J]. Journal of Tsinghua University(Science and Technology). 2017, 57(2): 147-152 https://doi.org/10.16511/j.cnki.qhdxxb.2017.22.006

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