Using Linguistic Anticipation to Improve the Quality of Speech Recognition in Robotic Systems

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Abstract

Anticipation is a phenomenon of a kind of forward-looking reflection that sometimes allows the subject to “see” the future. A number of experts believe that anticipation is an effective method for improving reading skills in children. Effective use of anticipation can significantly increase a person’s reading speed. The similarity of human learning processes and artificial neural algorithms suggests that introducing “anticipation”-based mechanisms into speech recognition algorithms can improve the quality of these systems. The article discusses the development of algorithms for modeling anticipation in speech recognition. It describes the proposed model and the setup of an experiment aimed at assessing the effect of anticipation mechanisms on the recognition result and discusses experimental findings and possible areas for further research on the topic.

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