Using neural network technologies in determining the emotional state of a person in oral communication

Abstract

The work presents a neural network of convolutional architecture that allows to recognize four human emotions (sadness, joy, anger, neutral) from spoken speech. Particular attention is paid to the formation of a dataset for training and testing the model, since at present there are practically no open speech databases for the study of paralinguistic phenomena (especially in Russian). This study uses the Dusha emotional speech database