Files
Document type
ArticleVersion
Accepted versionPublication date
Publication license
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/192860
Enhancing sentient embodied conversational agents with machine learning
Journal Title
Director/Tutor
Journal ISSN
Volume Title
Related resource
Abstract
Within the area of intelligent User Interfaces, we propose what we call Sentient Embodied Conversational Agents (SECAs): virtual characters able to engage users in complex conversations and to incorporate sentient capabilities similar to the ones humans have. This paper introduces SECAs together with their architecture and a publicly available software library that facilitates their inclusion in applications -such as educational and elder-care- requiring proactive and sensitive agent behaviours. In fact, we illustrate our proposal with a virtual tutor embedded in an educational application for children. The evaluation was performed in two stages: firstly, we tested a version with basic textual processing capabilities; and secondly, we evaluated a SECA with Machine-Learning enhanced user understanding capabilities. The results show a significant improvement in users' perception of the agent's understanding capability. Indeed, the Response Error Rate decreased from 22.31% to 11.46% when using ML techniques. Moreover, 99.33% of the participants consider the global experience of talking with the virtual tutor with sentient capabilities to be satisfactory.
Subject (English)
Citation
Citation
TELLOLS ASENSI, Dolça, et al. Enhancing sentient embodied conversational agents with machine learning. Pattern Recognition Letters. 2020. Vol. 129, num. 317-323. ISSN 0167-8655. [consulted: 14 of August of 2026]. Available at: https://hdl.handle.net/2445/192860