Evaluation of co-speech gestures grounded in word-distributed representation - Sasaki, Kosuke; Nishikawa, Jumpei; Morita, Junya (Frontiers in Robotics and AI, 2024)
The condition for artificial agents to possess perceivable intentions can be considered that they have resolved a form of the symbol grounding problem. Here, the symbol grounding is considered an achievement of the state where the language used by the agent is endowed with some quantitative meaning extracted from the physical world. To achieve this type of symbol grounding, we adopt a method for characterizing robot gestures with quantitative meaning calculated from word-distributed representations constructed from a large corpus of language. In this method, a "size image" of a word is generated by defining an axis (index) that discriminates the "size" of the word in the vector space of the word-distributed representation. The generated size images are converted into gestures generated by a physical artificial agent (robot). The robot's gesture can be set to reflect either the size of the word in terms of the amount of movement or in terms of its posture. To examine the perception of communicative intention in the robot that performs the gestures generated as described above, we examine human ratings on "the naturalness" obtained through an online survey. Based on the results of this study, the authors argue for the possibility of developing advanced artifacts that achieve human-like symbolic grounding.