Topic dependent language model based on on-line voting (言語理解とコミュニケーション)
スポンサーリンク
概要
- 論文の詳細を見る
In this paper, we propose an alternative approach to a topic dependent language model(LM), where the topic is decided by voting in an unsupervised manner. Latent Semantic Analysis(LSA)is employed to reveal hidden(latent)relations among nouns in the context word sequence. To decide the topic of an event, a fixed size word history sequence(window)is observed, and voting is then carried out based on noun class occurrences weighted by a confidence measure. Experiments on the Wall Street Journal corpus and Mainichi Shimbun(Japanese newspaper)corpus show that our proposed method gives better perplexity than the comparative baselines, including a word-based/class-based n-gram LM, their interpolated LM, a cache-based LM, and the Latent Dirichlet Allocation(LDA)-based topic dependent LM.
- 2009-12-14
著者
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Naptali Welly
Department of Information and Computer Sciences, Toyohashi University of Technology
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Tsuchiya Masatoshi
Information and Media Center, Toyohashi University of Technology
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Nakagawa Seiichi
Department of Information and Computer Sciences, Toyohashi University of Technology
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Tsuchiya Masatoshi
Information And Media Center Toyohashi University Of Technology
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Naptali Welly
Department Of Information And Computer Sciences Toyohashi University Of Technology
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Nakagawa Seiichi
Department Of Information And Computer Sciences Toyohashi University Of Technology
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Nakagawa Seiichi
Toyohashi Univ. Technol. Toyohashi‐shi Jpn
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Nakagawa Seiichi
Department Of Information And Computer Sciences Toyohashi University
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Nakagawa Seiichi
Department of Computer Science and Engineering, Toyohashi University of Technology
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NAPTALI Welly
Department of Computer Science and Engineering, Toyohashi University of Technology
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