Effect of Hidden Vector on the Speech of PRVA

Tetsuya Matsui, Iori Tani, Kazuto Sasai, Yukio Pegio Gunji

Research output: Contribution to journalArticlepeer-review

Abstract

This study aimed to propose a novel method for designing a product recommendation virtual agent (PRVA) that can keep users motivated to interact with the agent. In prior papers, many methods of keeping users motivated postulated real-time and multi-modal interactions. The proposed novel method can be used in one-direction interaction. We defined the notion of the “hidden vector,” that is, information that is not mentioned by a PRVA and that the user can suppose spontaneously. We conducted an experiment to verify the hypothesis that PRVAs having a hidden vector are more effective than other PRVAs. As a result, it was shown that PRVAs having a hidden vector were perceived as being more persuasive than other PRVAs and strongly motivated the users to use the PRVAs. From these results, the proposed method was shown to be effective.

Original languageEnglish
Article number627148
JournalFrontiers in Psychology
Volume12
DOIs
Publication statusPublished - 2021 May 28

Keywords

  • conversation agent
  • human-agent interaction
  • persuasion agent
  • product recommendation virtual agent
  • virtual agent

ASJC Scopus subject areas

  • Psychology(all)

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