Intelligent speech interaction of devices and human operators

Abstract

The article describes research and development of intelligent speech interaction systems between mobile lifting devices and their human operators. A general processing scheme, using several functional modules, for the interaction has been presented. The paper proposes an intelligent subsystem for assessment of human operator’s ability for efficient processing of information streams from many sources. The paper also formulates rigorously developed concepts of process information mining and assessment of task execution and correlated working conditions using hybrid neural networks. These methods enable a variety of analyzes of task parameters and working conditions and allow us to classify different process quality classes and safety condition types. Furthermore, the methodology allows us to determine regression of task execution quality assessment. The presented research offers the possibility of motivating and inspiring further development of the intelligent speech interaction system and methods that have been elaborated in this paper.