Title :
Keyword spotting based on mixed grammar model
Author :
Yining, Chen ; Jing, Liu ; Lin, Zhong ; Jia, Liu ; Runsheng, Liu
Author_Institution :
Dept. of Electron. Eng., Tsinghua Univ., Beijing, China
Abstract :
We present a novel keyword spotting method based on the mixed grammar model. By merging the filler model and the finite state grammar, two conventional technologies of keyword spotting, the mixed grammar model incorporates both a priori knowledge and the capability of covering all possible sentential forms in real speech, thus makes up for the weaknesses of both parental technologies. Experimental results show that the mixed grammar model excels the filler model in overall performance and the finite state grammar in robustness. The expansibility of the mixed grammar model is shown in its capacity of easy incorporation of further improvement of both the filler model and finite state grammar
Keywords :
grammars; speech recognition; experimental results; filler model; finite state grammar; keyword spotting method; mixed grammar model; speech recognition; Assembly; Automatic speech recognition; Buildings; Decoding; Hidden Markov models; Information systems; Intelligent structures; Merging; Robustness; Speech processing;
Conference_Titel :
Intelligent Multimedia, Video and Speech Processing, 2001. Proceedings of 2001 International Symposium on
Conference_Location :
Hong Kong
Print_ISBN :
962-85766-2-3
DOI :
10.1109/ISIMP.2001.925424
