Recognition of emotion intensity basing on neutral speech model

Abstract

Research in emotional speech recognition is generally focused on analysis of a set of primary emotions. However it is clear that spontaneous speech, which is more intricate comparing to acted out utterances, carries information about emotional complexity or degree of their intensity. This paper refers to the theory of Robert Plutchik, who suggested the existence of eight primary emotions. All other states are derivatives and occur as combinations, mixtures or compounds of the primary emotions. During the analysis Polish spontaneous speech database containing manually created confidence labels was implemented as a training and testing set. Classification results of four primary emotions (anger, fear, joy, sadness) and their intensities have been presented. The level of intensity is determined basing on the similarity of particular emotion to neutral speech. Studies have been conducted using prosodic features and perceptual coefficients. Results have shown that the proposed measure is effective in recognition of intensity of the predicted emotion.