Developing Enhanced Conversational Agents for Social Virtual Worlds

TL;DR

This paper introduces a methodology for creating embodied conversational agents in social virtual worlds that adapt their speech and emotional responses based on user interactions, enhancing social engagement.

Contribution

It presents a novel integrated approach combining AI, NLP, affective computing, and user modeling to develop adaptive conversational agents in virtual environments.

Findings

Agents successfully adapt to user characteristics

The system improves interaction quality over time

Embodied agents enhance user engagement in virtual worlds

Abstract

In this paper, we present a methodology for the development of embodied conversational agents for social virtual worlds. The agents provide multimodal communication with their users in which speech interaction is included. Our proposal combines different techniques related to Artificial Intelligence, Natural Language Processing, Affective Computing, and User Modeling. Firstly, the developed conversational agents. A statistical methodology has been developed to model the system conversational behavior, which is learned from an initial corpus and improved with the knowledge acquired from the successive interactions. In addition, the selection of the next system response is adapted considering information stored into users profiles and also the emotional contents detected in the users utterances. Our proposal has been evaluated with the successful development of an embodied conversational agent which has been placed in the Second Life social virtual world. The avatar includes the different models and interacts with the users who inhabit the virtual world in order to provide academic information. The experimental results show that the agents conversational behavior adapts successfully to the specific characteristics of users interacting in such environments.