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Collaborative Language Grounding Toward Situated Human-Robot Dialogue

机译:合作语言接地位于人机对话

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To enable situated human-robot dialogue, techniques to support grounded language communication are essential. One particular challenge is to ground human language to robot internal representation of the physical world. Although copresent in a shared environment, humans and robots have mismatched capabilities in reasoning, perception, and action. Their representations of the shared environment and joint tasks are significantly misaligned. Humans and robots will need to make extra effort to bridge the gap and strive for a common ground of the shared world. Only then, is the robot able to engage in language communication and joint tasks. Thus computational models for language grounding will need to take collaboration into consideration. A robot not only needs to incorporate collaborative effort from human partners to better connect human language to its own representation, but also needs to make extra collaborative effort to communicate its representation in language that humans can understand. To address these issues, the Language and Interaction Research group (LAIR) at Michigan State University has investigated multiple aspects of collaborative language grounding. This article gives a brief introduction to this research effort and discusses several collaborative approaches to grounding language to perception and action.
机译:为了启用位于人体机器人对话,支持接地语言通信的技术至关重要。一个特殊的挑战是将人类语言接地到物理世界的机器人内部代表。虽然在共享环境中,人类和机器人在推理,感知和行动方面具有不匹配的能力。他们对共享环境和联合任务的陈述是显着的未对准。人类和机器人需要额外努力弥合差距,努力为共享世界的共同之处。然后,只有机器人能够从事语言通信和联合任务。因此,语言接地的计算模型需要考虑合作。机器人不仅需要从人类合作伙伴那里融入合作努力,以更好地将人类语言与自己的代表联系起来,而且需要提出额外的合作努力,以传达人类可以理解的语言的代表性。为了解决这些问题,密歇根州立大学的语言和互动研究组(Lair)已经调查了协同语言接地的多个方面。本文简要介绍了这项研究努力,并讨论了若干合作方式,以对感知和行动接地语言。

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