HUMAN-COMPUTER INTERACTIONS BY USING RECOGNIZER OUTPUT VOTING ERROR REDUCTION SYSTEM

Abstract

Interaction between humans and machines is central to the field of computer science. many researchers whose focus is human-computer interaction are actually located in unrelated fields. In recent years, research into human-computer interfaces has shown a keen interest in the incorporation of emotions into conversation design. Hidden Markov Models (HMMs) have been used to distinguish emotions from speech signals.in this study has been explaining the optimizations and improvements of an emotion recognizer that works in conjunction with automated speech recognition. This study presents findings from experiments conducted on recorded and spontaneous emotional speech to show that a post-processing algorithm that incorporates various speech emotion recognizers have been successfully implemented.