Word and class dependency of N-gram language model (言語理解とコミュニケーション・第9回音声言語シンポジウム)

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概要

• 論文の詳細を見る

• We propose another way to calculate language model (LM) probability by making an assumption that the current word/the predicted word depends on word and class history. Experiment result on Wall Street Journal (WSJ) corpus shows that the proposed method is better than a traditional class-based n-gram LM.

• 社団法人電子情報通信学会の論文
• 2007-12-13

著者

• Tsuchiya Masatoshi

  Information And Media Center Toyohashi University Of Technology

• Naptali Welly

  Department Of Information And Computer Sciences Toyohashi University Of Technology

• Nakagawa Seiichi

  Department Of Information And Computer Sciences Toyohashi University Of Technology

• Nakagawa Seiichi

  Toyohashi Univ. Technol. Toyohashi‐shi Jpn

• Nakagawa Seiichi

  Department Of Information And Computer Sciences Toyohashi University

• Nakagawa Seiichi

  Department of Computer Science and Engineering, Toyohashi University of Technology

• NAPTALI Welly

  Department of Computer Science and Engineering, Toyohashi University of Technology

関連論文

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• Topic dependent language model based on clustering of noun word history
• Word and class dependency of N-gram language model (音声言語情報処理)
• Word and class dependency of N-gram language model (言語理解とコミュニケーション・第9回音声言語シンポジウム)
• Word and class dependency of N-gram language model (音声・第9回音声言語シンポジウム)
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