Automatic Diary Generation System including Information on Joint Experiences between Humans and Robots

TL;DR

This paper presents an automatic diary generation system that leverages joint human-robot experiences and large-scale language models to enhance robot-human interactions and improve robot likability.

Contribution

It introduces a novel diary generation method that incorporates joint experiences using language models, improving robot-human relationship perception.

Findings

Diaries with joint experience information received higher comfort and performance scores.

Humans preferred diaries that included shared experiences, indicating increased intimacy.

The system successfully generated personalized diaries based on interaction history.

Abstract

In this study, we propose an automatic diary generation system that uses information from past joint experiences with the aim of increasing the favorability for robots through shared experiences between humans and robots. For the verbalization of the robot's memory, the system applies a large-scale language model, which is a rapidly developing field. Since this model does not have memories of experiences, it generates a diary by receiving information from joint experiences. As an experiment, a robot and a human went for a walk and generated a diary with interaction and dialogue history. The proposed diary achieved high scores in comfort and performance in the evaluation of the robot's impression. In the survey of diaries giving more favorable impressions, diaries with information on joint experiences were selected higher than diaries without such information, because diaries with information on joint experiences showed more cooperation between the robot and the human and more intimacy from the robot.