Increasing Industrial Productivity by Employing a Smart Speech-Based Question Answering Assistant


This paper proposes a system design for a question-answering assistant, aiming to increase the productivity in industrial environments. The system is characterized by the fact that its components and domain specific knowledge are embedded on a given hardware platform locally. The effects of introducing a prototype-assistant on the productivity and the perceived workload are explored empirically by conducting experiments designed for this purpose. As a result, users were able to answer the given questions faster when using the prototype than when searching manually. Moreover, after employing the prototype, users reported their task to be less demanding, with a positive effect on the human-machine interaction.

Year: 2020
In session: (Speech) Assistents
Pages: 10 to 17