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Learning Word Groundings from Humans Facilitated by Robot Emotional Displays

David McNeill, Casey Kennington

Year
2020
Citations
2
Access
Open access

Abstract

In working towards accomplishing a human-level acquisition and understanding of language, a robot must meet two requirements: the ability to learn words from interactions with its physical environment, and the ability to learn language from people in settings for language use, such as spoken dialogue. In a live interactive study, we test the hypothesis that emotional displays are a viable solution to the cold-start problem of how to communicate without relying on language the robot does not–indeed, cannot–yet know. We explain our modular system that can autonomously learn word groundings through interaction and show through a user study with 21 participants that emotional displays improve the quantity and quality of the inputs provided to the robot.

Keywords

RobotWord (group theory)Computer scienceModular designHuman–computer interactionQuality (philosophy)Test (biology)Artificial intelligenceLinguistics

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