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

Akinori Ito, Toyomi Meguro, Shozo Makino, Motoyuki Suzuki

Research output: Contribution to journalConference article

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)207-210
Number of pages4
JournalProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Publication statusPublished - 2008 Dec 1
EventINTERSPEECH 2008 - 9th Annual Conference of the International Speech Communication Association - Brisbane, QLD, Australia
Duration: 2008 Sep 222008 Sep 26

Keywords

  • LSA
  • Thesaurus
  • Web search engine
  • Word similarity

ASJC Scopus subject areas

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

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