Intelligent System for Identifying Emotions on Audio Recordings Using Chalk Spectrograms

A neural network architecture is proposed to identify human emotions on audio recordings. Emotions are understood as fear, joy, sadness, anger, calmness, and neutrality. Library data are used for training. The psychophysical properties of an audio recording are saved by converting an audio file into...

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Bibliographic Details
Published in:Journal of computer & systems sciences international 2022-06, Vol.61 (3), p.407-412
Main Authors: Derevyagin, L. A., Makarov, V. V., Tsurkov, V. I., Yakovlev, A. N.
Format: Article
Language:English
Subjects:
Artificial Intelligence
Audio data
Chalk
Computer architecture
Control
Emotions
Engineering
Mechatronics
Multiplication
Neural networks
Organs
Robotics
Spectrograms
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Summary:A neural network architecture is proposed to identify human emotions on audio recordings. Emotions are understood as fear, joy, sadness, anger, calmness, and neutrality. Library data are used for training. The psychophysical properties of an audio recording are saved by converting an audio file into a spectrogram image with a chalk scale (chalk spectrogram). Such a spectrogram is an empirically chosen logarithmic dependence of the volume of sound vibrations perceived by human hearing organs on their frequency. Then methods for classifying graphic files are applied, including convolutional layers (the fragmental multiplication of pixel value matrices by the given matrices with the possible reduction of the picture dimension).
ISSN:1064-2307
1555-6530
DOI:10.1134/S1064230722030042