Inferring human beliefs and desires from their actions and the content of their utterances

Yuta Watanabe, Yosuke Fukuchi, Tomoyuki Maekawa, Shoya Matsumori, Michita Imai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

To create dialogue systems that provide information a user needs to know at an opportune moment, it is important to infer the user's mental states such as his/her beliefs and desires. There are two types of study on inferring beliefs and desires: one type infers them from actions and the other infers them from the content of utterances. However, a method to infer beliefs and desires from both kinds of inference in an integrated way has not yet been established. In this paper, we propose Multimodal Inference of Mind Simultaneous Contextualization and Interpreting (MIoM SCAIN), a system for sequentially inferring users' beliefs and desires on the basis of their walking behaviors and the content of their utterances. In our evaluation, we compared inferences of MIoM SCAIN with those of baselines that use either walking behaviors or the content of utterances. MIoM SCAIN's predictions showed more correlation with subjective judgements compared with the baselines, indicating that the inference of beliefs and desires from both walking behaviors and utterance content is possible.

Original languageEnglish
Title of host publicationHAI 2021 - Proceedings of the 9th International User Modeling, Adaptation and Personalization Human-Agent Interaction
PublisherAssociation for Computing Machinery, Inc
Pages391-395
Number of pages5
ISBN (Electronic)9781450386203
DOIs
Publication statusPublished - 2021 Nov 9
Event9th International User Modeling, Adaptation and Personalization Human-Agent Interaction, HAI 2021 - Virtual, Online, Japan
Duration: 2021 Nov 92021 Nov 11

Publication series

NameHAI 2021 - Proceedings of the 9th International User Modeling, Adaptation and Personalization Human-Agent Interaction

Conference

Conference9th International User Modeling, Adaptation and Personalization Human-Agent Interaction, HAI 2021
Country/TerritoryJapan
CityVirtual, Online
Period21/11/921/11/11

Keywords

  • Bayesian inference
  • Dialogue system
  • Human computer interaction
  • Partially observable markov decision processes
  • Theory of mind

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Human-Computer Interaction

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