Presentation | 2008-12-10 Language Model Adaptation by Topic Model Based on Sequence of Words Atsushi SAKO, Tetsuya TAKIGUCHI, Yasuo ARIKI, |
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Abstract(in English) | It is important to consider semantics for reductions of recognition errors unlike humans or understanding meanings and contents. To accommodate these problems, Latent Semantic Analysis (LSA) or Probabilistic LSA have been proposed. However these methods are based on Bag-of-words techniques. For more sophisticated analysis, it needs to consider a sequence of words in a document. In this paper, we propose the method based on Kernel PCA and Dynamic Time Alignment Kernel in order to consider a sequence of words. Preliminary experimental results shows the proposed method can separete clearly a sequence of right turn/left turn prots data. Moreover, experimental results of language corpus shows the reduction of perplexity. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Latent Semantic Analysis / Kernel PCA / Topic Model |
Paper # | NLC2008-66,SP2008-121 |
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Committee | NLC |
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Conference Date | 2008/12/2(1days) |
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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) | Language Model Adaptation by Topic Model Based on Sequence of Words |
Sub Title (in English) | |
Keyword(1) | Latent Semantic Analysis |
Keyword(2) | Kernel PCA |
Keyword(3) | Topic Model |
1st Author's Name | Atsushi SAKO |
1st Author's Affiliation | Guraduate School of Science and Technology, Kobe University:Guraduate School of Engineering, Kobe University() |
2nd Author's Name | Tetsuya TAKIGUCHI |
2nd Author's Affiliation | / |
3rd Author's Name | Yasuo ARIKI |
3rd Author's Affiliation | |
Date | 2008-12-10 |
Paper # | NLC2008-66,SP2008-121 |
Volume (vol) | vol.108 |
Number (no) | 337 |
Page | pp.pp.- |
#Pages | 6 |
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