Method for Reducing the Feature Space Dimension in Speech Emotion Recognition Using Convolutional Neural Networks

• Published in: Automation and remote control Vol. 83; no. 6; pp. 857 - 868
• Main Authors: Iskhakova, A. O., Vol’f, D. A., Meshcheryakov, R. V.
• Format: Journal Article
• Language: English
• Published: Moscow Pleiades Publishing 01.06.2022; Springer Nature B.V
• Subjects: Algorithms; Artificial neural networks; CAE) and Design; Calculus of Variations and Optimal Control; Optimization; Computer-Aided Engineering (CAD; Control; Emotion recognition; Emotional factors; Emotions; Machine learning; Mathematics; Mathematics and Statistics; Mechanical Engineering; Mechatronics; Robotics; Speech recognition; Systems Theory; Thematic Issue; speech signal; detection of aggression; classification of speech signals; recognition of speech emotions; convolutional neural network; sound; socio-cyber-physical system; identification of emotional state

We consider the architectures of convolutional neural networks used to assess the emotional state of a person by their speech. The problem of increasing the efficiency of emotion recognition by reducing the computational complexity of this process is solved. To this end, we propose a method transfor...