Far-Field Audio-Visual Scene Perception of Multi-Party Human-Robot Interaction for Children and Adults

Human-robot interaction (HRI) is a research area of growing interest with a multitude of applications for both children and adult user groups, as, for example, in edutainment and social robotics. Crucial, however, to its wider adoption remains the robust perception of HRI scenes in natural, untethered, and multi-party interaction scenarios, across user groups. Towards this goal, we investigate three focal HRI perception modules operating on data from multiple audio-visual sensors that observe the HRI scene from the far-field, thus bypassing limitations and platform-dependency of contemporary robotic sensing. In particular, the developed modules fuse intra- and/or inter-modality data streams to perform: (i) audio-visual speaker localization; (ii) distant speech recognition; and (iii) visual recognition of hand-gestures. Emphasis is also placed on ensuring high speech and gesture recognition rates for both children and adults. Development and objective evaluation of the three modules is conducted on a corpus of both user groups, collected by our far-field multisensory setup, for an interaction scenario of a question-answering “guess-the-object” collaborative HRI game with a “Furhat” robot. In addition, evaluation of the game incorporating the three developed modules is reported. Our results demonstrate robust far-field audio-visual perception of the multi-party HRI scene.