A Real-Time Robot-Based Auxiliary System for Risk Evaluation of COVID-19 Infection

Wenqi Wei, Jianzong Wang, Jiteng Ma, Ning Cheng, Jing Xiao
2020 Interspeech 2020  
In this paper, we propose a real-time robot-based auxiliary system for risk evaluation of COVID-19 infection. It combines real-time speech recognition, temperature measurement, keyword detection, cough detection and other functions in order to convert live audio into actionable structured data to achieve the COVID-19 infection risk assessment function. In order to better evaluate the COVID-19 infection, we propose an end-to-end method for cough detection and classification for our proposed
more » ... m. It is based on real conversation data from human-robot, which processes speech signals to detect cough and classifies it if detected. The structure of our model are maintained concise to be implemented for real-time applications. And we further embed this entire auxiliary diagnostic system in the robot and it is placed in the communities, hospitals and supermarkets to support COVID-19 testing. The system can be further leveraged within a business rules engine, thus serving as a foundation for real-time supervision and assistance applications. Our model utilizes a pretrained, robust training environment that allows for efficient creation and customization of customer-specific health states.
doi:10.21437/interspeech.2020-2105 dblp:conf/interspeech/WeiWMCX20 fatcat:24vkac4qpfag5io2fh5xyu5wxa