Presentation 2009-01-29
Error Detection in Speech Recognition using CRF Based on Various Linguistic Features
Tomohiko MATSUMOTO, Atsushi SAKO, Tetsuya TAKIGUCHI, Yasuo ARIKI,
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Abstract(in English) Recently, a learning method of n-gram showing error tendency is focused on. In this method, it is difficult to learn low frequency n-gram appropriately. On the other hand, error detection method for content words was proposed that uses semantic similarity in neighboring recognition result. In this paper, we especially examine semantic score and propose a method for speech recognition error detection that integrates these information. As a result of evaluation experiment using the Corpus of Spontaneous Japanese, error detecting performance was improved for content words in particular. Moreover, semantic score is effectively used by combining with term-weight.
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Keyword(in English) Speech Recognition Error Detection / Confidence Measure / Linguistic feature / Semantic feature / CRF
Paper # SP2008-127
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Committee SP
Conference Date 2009/1/22(1days)
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Registration To Speech (SP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Error Detection in Speech Recognition using CRF Based on Various Linguistic Features
Sub Title (in English)
Keyword(1) Speech Recognition Error Detection
Keyword(2) Confidence Measure
Keyword(3) Linguistic feature
Keyword(4) Semantic feature
Keyword(5) CRF
1st Author's Name Tomohiko MATSUMOTO
1st Author's Affiliation Graduate School of Engineering, Kobe University()
2nd Author's Name Atsushi SAKO
2nd Author's Affiliation Graduate School of Engineering, Kobe University
3rd Author's Name Tetsuya TAKIGUCHI
3rd Author's Affiliation Organization of Advanced Science and Technology, Kobe University
4th Author's Name Yasuo ARIKI
4th Author's Affiliation Organization of Advanced Science and Technology, Kobe University
Date 2009-01-29
Paper # SP2008-127
Volume (vol) vol.108
Number (no) 422
Page pp.pp.-
#Pages 6
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