Improved lattice-based speech keyword spotting algorithm

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Abstract An improved lattice-based speech keyword spotting system was developed from the Gaussian mixture model and an improved N-best speech recognition algorithm. First, tests were used to evaluate different simplified structures of Gaussian mixture models. Then, an N-best token passing algorithm was developed from the classic token passing algorithm using some unique pronunciation rules for the Chinese language. These two modifications improve the performance of both the 1-best and N-best speech recognition candidates. Finally, a key word spotting system was developed based on an N-best lattice to show the effectiveness of these improvements.

Keywords speech keyword spotting multi-candidate lattice Gaussian mixture model compute unified device architecture (CUDA) triphone model

ZTFLH:

TP391.4

Issue Date: 15 May 2015

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	XIAO Xi
	WANG Jingqian

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XIAO Xi,WANG Jingqian. Improved lattice-based speech keyword spotting algorithm[J]. Journal of Tsinghua University(Science and Technology), 2015, 55(5): 508-513.

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http://jst.tsinghuajournals.com/EN/ OR http://jst.tsinghuajournals.com/EN/Y2015/V55/I5/508

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