Presentation	1993/12/10 Topic Focusing Mechanism for Speech Recognition based on Probabilistic Grammar and Topic Markov Model Takeshi Kawabata,
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Abstract(in English)	Speech conversation is the most comfortable interface for human- machine communication.For this purpose,effective natural language processing technologies are necessary.This paper describes a new stochastic topic focusing mechanism for reducing the perplexity of natural spoken languages.The predictive CFG parser analyzes input speech and generates grammar-rule sequences.These rule sequences drive the topic hidden Markov model and the current topic is estimated as HMM state distribution.The CFG rule probabilities are dynamically changed according to this topic state distribution.The evaluation experiments using a large dialog text database shows that the proposed topic focusing mechanism effectively reduce the task perplexity.
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Keyword(in English)	Natural language / Topic focusing / Speech understanding / JUNO
Paper #	NLC93-55
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Conference Information
Committee	NLC
Conference Date	1993/12/10(1days)
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Paper Information
Registration To	Natural Language Understanding and Models of Communication (NLC)
Language	JPN
Title (in Japanese)	(See Japanese page)
Sub Title (in Japanese)	(See Japanese page)
Title (in English)	Topic Focusing Mechanism for Speech Recognition based on Probabilistic Grammar and Topic Markov Model
Sub Title (in English)
Keyword(1)	Natural language
Keyword(2)	Topic focusing
Keyword(3)	Speech understanding
Keyword(4)	JUNO
1st Author's Name	Takeshi Kawabata
1st Author's Affiliation	NTT Basic Research Laboratories()
Date	1993/12/10
Paper #	NLC93-55
Volume (vol)	vol.93
Number (no)	367
Page	pp.pp.-
#Pages	7
Date of Issue