Presentation 1995/12/15
Language model acquisition from a text corpus for speech understanding
Tatsuo Matsuoka, Robert Hasson, Michael Barlow, Sadaoki Furui,
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Abstract(in English) Speech understanding can be viewed as a translation problem from natural language into semantic language. This paper describes automatic acquisition of a language model by using a text corpus, which translates natural language into semantic language for speech understanding. A stochastic method for language modeling is proposed for machine translation using a parallel text corpus. This method can be used in speech understanding, but input and output languages should be modeled concisely in order to estimate a reliable translation language model. This paper proposes a method for reducing the number of grammar rules while maintaining the original coverage. This method was shown to be effective by experiments using the ARPA ATIS task.
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Keyword(in English) Speech understanding / Translation / Language modeling / Natural language / Semantic language
Paper # NLC95-59,SP95-94
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Committee NLC
Conference Date 1995/12/15(1days)
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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) Language model acquisition from a text corpus for speech understanding
Sub Title (in English)
Keyword(1) Speech understanding
Keyword(2) Translation
Keyword(3) Language modeling
Keyword(4) Natural language
Keyword(5) Semantic language
1st Author's Name Tatsuo Matsuoka
1st Author's Affiliation NTT Human Interface Laboratories()
2nd Author's Name Robert Hasson
2nd Author's Affiliation NTT Human Interface Laboratories
3rd Author's Name Michael Barlow
3rd Author's Affiliation NTT Human Interface Laboratories
4th Author's Name Sadaoki Furui
4th Author's Affiliation NTT Human Interface Laboratories
Date 1995/12/15
Paper # NLC95-59,SP95-94
Volume (vol) vol.95
Number (no) 429
Page pp.pp.-
#Pages 6
Date of Issue