Companion robots should perceive speech, recognize objects in the real world, and further react with speech utterances and nonverbal communicative cues. Robots should also remember the interaction history and accumulate knowledge from external text sources: news, blogs, and e-mails. We have designed a conceptual representation system for a companion robot, able to support this list of interactive tasks. The system includes a speech processing component and operates with semantic representations: sets of semantic markers, assigned to valencies within sentence predications. The reaction support system inherits a classic production architecture and consists of scripts, sensitive to rational or emotional stimuli. The general architecture is based on parallel processing of scripts, it may trigger several behavioral reactions in response to a stimulus, and after that it combines speech output and nonverbal reactions of these scripts on the robot, thus, constructing compound and rich behavior. Semantic representations and scripts are also used to index incoming utterances in a memory base.

伴侣机器人应该感知语音，识别现实世界中的物体，并进一步对语音发声和非语言交流提示做出反应。机器人还应该记住交互历史，并从外部文本源（新闻，博客和电子邮件）中积累知识。我们为伴侣机器人设计了一种概念表示系统，能够支持此交互式任务列表。该系统包括语音处理组件，并以语义表示进行操作：语义标记集，分配给句子谓词内的效价。反应支持系统继承了经典作品架构，由对理性或情感刺激敏感的脚本组成。通用架构基于脚本的并行处理，它可能会响应刺激而触发多种行为反应，然后在机器人上将这些脚本的语音输出和非语言反应相结合，从而构建复合行为和丰富行为。语义表示和脚本也用于索引存储库中的传入话语。