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Software systems and computational methods
Reference:

Sidorov K.V., Filatova N.N. Automatic recognition of human emotions based on the reconstruction of the speech samples attractors

Abstract: The article reviews the methods of automatic pattern recognition of the speech signals recorded at the moments when announ cers proved positive emotions from speech samples on the same subjects recorded in a testees’ neutral state. This article investigates the abilities of nonlinear dynamics methods for evaluation of informative indicators of emotional state. Studies were performed on the basis of analyzing the reconstruction of attractors of the speech signal. The authors analyzed different ways of selecting optimal parameter values for the reconstruction of the attractor (the time delay between the elements of the time series and embedding dimension). Authors proposed the new quan titative criteria for classifying samples of the speech signal of a person experiencing emo tions based on the estimates of the maximum vector reconstruction of the attractor in four quadrants. The research was based on frag ments of the Russian-language database (Tver). A model of emotional body language, which consists of a database of two levels (phrases and phonemes) was formed and served as a basis for evaluation of the efÞ cie n cy of the developed software module of the automatic recognition of human emotions.

Keywords:

Software, speech, speech signal, emotional state, time series, emotion, emotion recognition, nonlinear dynamics, attractor reconstruction, classification

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