Arthur: a new ECA that uses Memory to improve Communication

TL;DR

Arthur is an embodied conversational agent that enhances communication by recognizing users' emotions and identities, utilizing an artificial memory system to improve interaction quality based on experimental evidence.

Contribution

The paper introduces Arthur, a novel ECA that integrates emotion recognition, identity detection, and memory retrieval to advance human-computer interaction.

Findings

Memory system improves user engagement

Emotion recognition enhances communication quality

Experimental results show positive user impact

Abstract

This article proposes an embodied conversational agent named Arthur. In addition to being able to talk to a person (using text and voice), he is also able to recognize the person he is talking to and detect his/her expressed emotion through facial expressions. Arthur uses these skills to improve communication with the user, also using his artificial memory, which stores and retrieves data about events and facts, based on a human memory model. We conducted some experiments to collect quantitative and qualitative information, which show that our model provides a consistent impact on users.