School of Computer Sciences, University Science of Malaysia, Penang 11900, Malaysia.
Sensors (Basel). 2013 Aug 13;13(8):10519-38. doi: 10.3390/s130810519.
We describe the work on infusion of emotion into a limited-task autonomous spoken conversational agent situated in the domestic environment, using a need-inspired task-independent emotion model (NEMO). In order to demonstrate the generation of affect through the use of the model, we describe the work of integrating it with a natural-language mixed-initiative HiFi-control spoken conversational agent (SCA). NEMO and the host system communicate externally, removing the need for the Dialog Manager to be modified, as is done in most existing dialog systems, in order to be adaptive. The first part of the paper concerns the integration between NEMO and the host agent. The second part summarizes the work on automatic affect prediction, namely, frustration and contentment, from dialog features, a non-conventional source, in the attempt of moving towards a more user-centric approach. The final part reports the evaluation results obtained from a user study, in which both versions of the agent (non-adaptive and emotionally-adaptive) were compared. The results provide substantial evidences with respect to the benefits of adding emotion in a spoken conversational agent, especially in mitigating users' frustrations and, ultimately, improving their satisfaction.
我们描述了在家庭环境中使用需要启发的任务独立情感模型（NEMO）为有限任务自主口语对话代理注入情感的工作。为了展示通过使用模型生成情感的效果，我们描述了将其与自然语言混合主动 HiFi 控制口语对话代理（SCA）集成的工作。NEMO 和主机系统在外部进行通信，不需要像大多数现有对话系统那样修改对话管理器以实现自适应。本文的第一部分涉及 NEMO 和主机代理之间的集成。第二部分总结了从对话特征（非常规来源）中自动预测情感（挫折感和满足感）的工作，旨在朝着更以用户为中心的方法迈进。最后一部分报告了用户研究中获得的评估结果，其中比较了两个版本的代理（非自适应和情感自适应）。结果提供了大量证据，证明在口语对话代理中添加情感的好处，特别是在减轻用户的挫折感并最终提高他们的满意度方面。
