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 Japanese) | (See Japanese page) |
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 |
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Conference Date | 2011/12/12(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Natural Language Understanding and Models of Communication (NLC) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
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 |
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