Robots Learn Social Skills: End-to-End Learning of Co-Speech Gesture Generation for Humanoid Robots
Robots Learn Social Skills: End-to-End Learning of Co-Speech Gesture Generation for Humanoid Robots
复制标题
机器人学习社交技能：人形机器人协同语音手势生成的端到端学习
DOI：
--
复制
发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Geehyuk Lee
中科院分区：
文献类型：
--
作者：
Youngwoo Yoon;Woo;Minsu Jang;Jaeyeon Lee;Jaehong Kim;Geehyuk Lee
协同语音手势增强了人与人之间以及人与机器人之间的交互体验。大多数现有的机器人使用基于规则的语音手势关联，但这需要人类的劳动和专家的先验知识来实现。我们提出了一个基于学习的共同语音手势生成，它是从52个小时的TED演讲中学习到的。提出的端到端神经网络模型由一个用于语音文本理解的编码器和一个用于生成一系列手势的解码器组成。该模型成功地产生了各种手势，包括符号手势、隐喻手势、指示手势和节拍手势。在主观评价中，参与者报告说这些手势与人类相似，并且与演讲内容相匹配。我们还演示了与NAO机器人实时工作的协同语音手势。
Co-speech gestures enhance interaction experiences between humans as well as between humans and robots. Most existing robots use rule-based speech-gesture association, but this requires human labor and prior knowledge of experts to be implemented. We present a learning-based co-speech gesture generation that is learned from 52 h of TED talks. The proposed end-to-end neural network model consists of an encoder for speech text understanding and a decoder to generate a sequence of gestures. The model successfully produces various gestures including iconic, metaphoric, deictic, and beat gestures. In a subjective evaluation, participants reported that the gestures were human-like and matched the speech content. We also demonstrate a co-speech gesture with a NAO robot working in real time.
影响因子：
4.7
作者：
Salem, Maha;Eyssel, Friederike;Joublin, Frank
通讯作者：
Joublin, Frank