Chae, Yu-Jung Nam, Changjoo Yang, Daseul Sin, HunSeob 김창환 박성기 2024-01-12T03:00:20Z 2024-01-12T03:00:20Z 2022-06-07 2022-09 0921-8890 https://pubs.kist.re.kr/handle/201004/76625 https://www.sciencedirect.com/science/article/pii/S0921889022000884 We propose a methodology for a robot to automatically generate felicitous co-speech gestures corresponding to robot utterances. First, the proposed method determines the part of a given robot utterance, where the robot makes a gesture by doing a morphemic analysis on the sentence of utterance. The part is herein called an expression unit. The method then predicts a gesture type to characterize the expression unit in the sense of conveying thoughts and feelings. The gesture type is selected from the four types of iconic, metaphoric, beat, and deictic categorized by McNeill by performing morphemic analysis on the sentence. A gesture proper to the gesture type is retrieved from a database of motion primitives that are built with predefined a limited number of words. For retrieving, Word2Vec is applied to estimate word similarity between the predefined words in the database and words in the expression unit such that the method can deal with an arbitrary sentence and generate an appropriate gesture for similar words in meaning. English Elsevier BV Generation of co-speech gestures of robot based on morphemic analysis Article 10.1016/j.robot.2022.104154 1 Robotics and Autonomous Systems, v.155 Robotics and Autonomous Systems 155 Y scie scopus 000833416900004 Automation & Control Systems Computer Science, Artificial Intelligence Robotics Automation & Control Systems Computer Science Robotics Article Human-robot interaction Co-speech gesture generation Machine learning Morphemic analysis Word embedding