Speech Interaction to Control a Hands-Free Delivery Robot for High-Risk Health Care Scenarios

Abstract

The Covid-19 pandemic has had a widespread effect across the globe. The major effect on health-care workers and the vulnerable populations they serve has been of particular concern. Near-complete lockdown has been a common strategy to reduce the spread of the pandemic in environments such as live-in care facilities. Robotics is a promising area of research that can assist in reducing the spread of covid-19, while also preventing the need for complete physical isolation. The research presented in this paper demonstrates a speech-controlled, self-sanitizing robot that enables the delivery of items from a visitor to a resident of a care facility. The system is automated to reduce the burden on facility staff, and it is controlled entirely through hands-free audio interaction in order to reduce transmission of the virus. We demonstrate an end-to-end delivery test, and an in-depth evaluation of the speech interface. We also recorded a speech dataset with two conditions: the talker wearing a face mask and the talker not wearing a face mask. We then used this dataset to evaluate the speech recognition system. This enabled us to test the effect of face masks on speech recognition interfaces in the context of autonomous systems.