A real-time task-oriented speech understanding system using keyword-spotting

Authors:
Hiroyuki Tsuboi;Yoichi Takebayashi
Affiliations:
Toshiba Corporation, Kansai Research Laboratory, Kawasaki, Japan;Toshiba Corporation, Research & Development Center, Kawasaki, Japan
Venue:
ICASSP'92 Proceedings of the 1992 IEEE international conference on Acoustics, speech and signal processing - Volume 1
Year:
1992

Citing 7
Cited 1

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Abstract

This paper describes a real-time task-oriented spontaneous speech understanding system, which extracts semantic content from the spotted keyword lattice using a newly developed LR parser. The parser is driven whenever a keyword candidate is spotted. The keyword candidates are fed into the parser to construct a semantic structure using a grammar. This efficient parsing enables real-time initialstate-free speech understanding. The parser comprises the following functional components: initial-state processing to check if a keyword candidate can be an initial keyword and to create a parsing stack, keyword connection processing to check if a current keyword can connect with a subsentence candidate, sentence acceptance processing to check if subsentence candidates can be accepted as a sentence candidate.