让虚拟世界中的对话代理能听懂人话并感知情绪，自动调整回应。
Developing Enhanced Conversational Agents for Social Virtual Worlds
- 融合AI、自然语言与情感计算，实现多模态对话。
- 代理根据用户情绪和资料动态选择回复，适应性强。
- 已在Second Life中成功部署，适合社交虚拟场景研究。
本文提出一种面向社交虚拟世界的具身对话代理开发方法。代理支持多模态交互，包含语音对话。方案整合人工智能、自然语言处理、情感计算与用户建模技术。首先构建对话代理系统，采用统计方法建模其对话行为，初始基于语料库学习，并在后续交互中持续优化。响应选择结合用户画像信息及用户话语中的情感内容进行动态调整。该方案已成功应用于Second Life社交虚拟世界，部署具身代理以提供学术信息。实验结果表明，代理的对话行为能有效适应此类环境中用户的特定特征。
原文摘要 · Abstract (English)
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.
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