Discrimination of task-related words for vocabulary design of spoken dialog systems

Akinori Ito, Toyomi Meguro, Shozo Makino, Motoyuki Suzuki

研究成果: Conference article査読

1 被引用数 (Scopus)

抄録

This paper describes a method used to determine if a specific word is related to a certain spoken dialog task. In most ordinary spoken dialog systems, only the words that are actually used to achieve the task are included in the vocabulary. Therefore, the system cannot recognize utterances that contain OOV words that are related to the task. Therefore, we developed a method for determining the words that are related to a specified task in order to augment the system's vocabulary. Our method is based on word similarity. We examined three similarities: word occurrence frequency on the Web, distance in a thesaurus and word similarity using LSA. The experiment revealed that the thesaurus-based and LSA-based methods have an OOV problem. To solve the problem, we developed a way to combine these two methods with the Web-based method. In addition, we tried combining the methods using the AdaBoost algorithm.

本文言語English
ページ(範囲)207-210
ページ数4
ジャーナルProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
出版ステータスPublished - 2008 12 1
イベントINTERSPEECH 2008 - 9th Annual Conference of the International Speech Communication Association - Brisbane, QLD, Australia
継続期間: 2008 9 222008 9 26

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Signal Processing
  • Software
  • Sensory Systems

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