Improvement of the Human Emotional State Identification Algorithm Using MFCC
https://doi.org/10.17586/0021-3454-2024-67-9-731-740
Abstract
An approach to the implementation of an algorithm for the emotional state of a person using convolutional neural networks is presented. Based on the general concept of scientific research, a variant of complicating the hierarchy of identifiable emotions is considered. A comparative analysis of the application of the windowed Fourier transform and the MFCC algorithm as a tool for processing information data is carried out. The variant of complication of the proposed method is considered as a logical transition from a simpler mathematical apparatus, presented in the form of a windowed Fourier transform to the use of mel-frequency cepstral coefficients. This allowed to form a more informative input data set without complicating the neural network architecture, the methodology of scientific research was adjusted and, using an idealized database, the accuracy of identification close to 100% was achieved. The rationale for using Deep Network Designer as a tool for creating neural network architecture is given.
About the Authors
V. V. Semenuk
Platov South-Russian State Polytechnic University
Russian Federation
Russian Federation
Victoria V. Semenuk, Post-Graduate Student
Department of Computer Software
Novocherkassk
M. V. Skladchikov
Donetsk National Technical University
Russian Federation
Russian Federation
Maxim V. Skladchikov, Post-Graduate Student
Department of Electric Drives and Automation of Industrial Installations
Donetsk
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Review
For citations:
Semenuk V.V., Skladchikov M.V. Improvement of the Human Emotional State Identification Algorithm Using MFCC. Journal of Instrument Engineering. 2024;67(9):731-740. (In Russ.) https://doi.org/10.17586/0021-3454-2024-67-9-731-740
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