Eliciting User Food Preferences in terms of Taste and Texture in Spoken Dialogue Systems

Jie Zeng, Yukiko I. Nakano, Takeshi Morita, Ichiro Kobayashi, Takahira Yamaguchi

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

1 Citation (Scopus)

Abstract

Food preference varies from person to person and is not easy to verbalize. This study proposes a dialogue system that elicits the user’s food preference through human-robot interaction. First, as the default knowledge of the dialogue system, we determined the ingredients of each dish from a large-scale recipe database, and collected the taste and texture of each dish and its ingredients by analyzing a large number of Twitter messages. Subsequently, the dialogue system asks questions to elicit the user’s preferred taste/texture of the food by using the default knowledge base, while employing frame-based dialogue management. Finally, we created a food vector space that represents the relationship between the dish names, ingredients, and taste/texture expressions. We also discuss the possibility of using this vector space in dish recommendation.

Original languageEnglish
Title of host publicationMHFI 2018 - 3rd Workshop on Multisensory Approaches to Human-Food Interaction
EditorsCarlos Velasco, Anton Nijholt, Marianna Obrist, Katsunori Okajima, Charles Spence
PublisherAssociation for Computing Machinery, Inc
ISBN (Electronic)9781450360746
DOIs
Publication statusPublished - 2018 Oct 16
Event3rd Workshop on Multisensory Approaches to Human-Food Interaction, MHFI 2018, in conjunction with the 20th ACM International Conference on Multimodal Interaction, ICMI 2018 - Boulder, United States
Duration: 2018 Oct 16 → …

Publication series

NameMHFI 2018 - 3rd Workshop on Multisensory Approaches to Human-Food Interaction

Other

Other3rd Workshop on Multisensory Approaches to Human-Food Interaction, MHFI 2018, in conjunction with the 20th ACM International Conference on Multimodal Interaction, ICMI 2018
CountryUnited States
CityBoulder
Period18/10/16 → …

Keywords

  • Spoken dialogue system
  • Taste and texture
  • Twitter

ASJC Scopus subject areas

  • Hardware and Architecture
  • Food Science
  • Social Psychology
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Cultural Studies
  • Human-Computer Interaction

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  • Cite this

    Zeng, J., Nakano, Y. I., Morita, T., Kobayashi, I., & Yamaguchi, T. (2018). Eliciting User Food Preferences in terms of Taste and Texture in Spoken Dialogue Systems. In C. Velasco, A. Nijholt, M. Obrist, K. Okajima, & C. Spence (Eds.), MHFI 2018 - 3rd Workshop on Multisensory Approaches to Human-Food Interaction (MHFI 2018 - 3rd Workshop on Multisensory Approaches to Human-Food Interaction). Association for Computing Machinery, Inc. https://doi.org/10.1145/3279954.3279959