A graph-based spoken dialog strategy utilizing multiple understanding hypotheses

Norihide Kitaoka, Yuji Kinoshita, Sunao Hara, Chiyomi Miyajima, Kazuya Takeda

Research output: Contribution to journalArticlepeer-review


We regarded a dialog strategy for information retrieval as a graph search problem and proposed several novel dialog strategies that can recover from misrecognition through a spoken dialog that traverses the graph. To recover from misrecognition without seeking confirmation, our system kept multiple understanding hypotheses at each turn and searched for a globally optimal hypothesis in the graph whose nodes express understanding states across user utterances in a whole dialog. In the search, we used a new criterion based on efficiency in information retrieval and consistency with understanding hypotheses, which is also used to select an appropriate system response. We showed that our system can make more efficient and natural dialogs than previous ones.

Original languageEnglish
Pages (from-to)1-10
Number of pages10
JournalTransactions of the Japanese Society for Artificial Intelligence
Issue number1
Publication statusPublished - 2014


  • Consistency measure
  • Efficiency measure
  • Misrecognition
  • Response generation
  • Spoken dialog strategy

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence


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