International Conference on Agents and Artificial Intelligence

Agents and Artificial Intelligence pp 119-136 | Cite as

Statistical Response Method and Learning Data Acquisition using Gamified Crowdsourcing for a Non-task-oriented Dialogue Agent

  • Michimasa Inaba
  • Naoyuki Iwata
  • Fujio Toriumi
  • Takatsugu Hirayama
  • Yu Enokibori
  • Kenichi Takahashi
  • Kenji Mase
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8946)

Abstract

This paper presents a proposal of a construction method for non-task-oriented dialogue agents (chatbots) that are based on the statistical response method. The method prepares candidate utterances in advance. From the data, it learns which utterances are suitable for context. Therefore, a dialogue agent constructed using our method automatically selects a suitable utterance depending on a context from candidate utterances. This paper also proposes a low-cost quality-assured method of learning data acquisition for the proposed response method. The method uses crowdsourcing and brings game mechanics to data acquisition.

Results of an experiment using learning data obtained using the proposed data acquisition method demonstrate that the appropriate utterance is selected with high accuracy.

Keywords

Dialogue agent Chatbots Crowdsourcing Gamification. 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Michimasa Inaba
    • 1
  • Naoyuki Iwata
    • 2
  • Fujio Toriumi
    • 3
  • Takatsugu Hirayama
    • 2
  • Yu Enokibori
    • 2
  • Kenichi Takahashi
    • 1
  • Kenji Mase
    • 2
  1. 1.Graduate School of Information SciencesHiroshima City UniversityHiroshimaJapan
  2. 2.Graduate School of Information SciencesNagoya UniversityNagoyaJapan
  3. 3.School of EngineeringUniversity of TokyoTokyoJapan

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