Speech Enhanced Imitation Learning and Task Abstraction for Human-Robot Interaction


In this short paper, we show how to learn interaction primitives and networks from long interactions by taking advantage of language and speech markers. The speech markers are obtained from free speech that accompanies the demonstration. We perform experiments to show the value of using speech markers for learning interaction primitives.

Conference on Intelligent Robots and Systems (IROS)