Presentation 2011/12/12
Using Augmented Syllable lattice and Reduction of the n-gram Index for Spoken Term Detection
KEISUKE IWAMI, KAZUMASA YAMAMOTO, SEIICHI NAKAGAWA,
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Abstract(in English) We can find the information with an existing textual search engine if the target data consist of text information such as news and newspaper, but efficient spoken term detection (STD) method is not currently the established, because spoken document has specific problems such as some recognition errors and out-of-vocabulary(OOV) terms. Therefore, sub-word unit based recognition and retrieval methods have been proposed. In our previous work, we proposed a very fast Japanese STD system that is robust for considering OOV words and mis-recognition of sub-units. We used individual syllables as sub-word unit in continuous speech recognition and an n-gram sequence of syllables in a recognized syllable-based lattice. Specially, in this paper, we introduced a dummy syllable symbol for attacking the substitution errors and the index reduction.
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Paper # Vol.2011-SLP-89 No.5
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Committee NLC
Conference Date 2011/12/12(1days)
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Registration To Natural Language Understanding and Models of Communication (NLC)
Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) Using Augmented Syllable lattice and Reduction of the n-gram Index for Spoken Term Detection
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1st Author's Name KEISUKE IWAMI
1st Author's Affiliation Toyohashi University of Technology()
2nd Author's Name KAZUMASA YAMAMOTO
2nd Author's Affiliation Toyohashi University of Technology
3rd Author's Name SEIICHI NAKAGAWA
3rd Author's Affiliation Toyohashi University of Technology
Date 2011/12/12
Paper # Vol.2011-SLP-89 No.5
Volume (vol) vol.111
Number (no) 364
Page pp.pp.-
#Pages 8
Date of Issue