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Regular version of the site

Book chapter

Детектирование эмоций в мультимедиа контенте

С. 852-857.
А. С. Попова, А. Г. Рассадин, А. А. Пономаренко

In this paper we consider the automatic emotions recognition problem, especially the case of digital audio signal processing. We consider and verify an approach in which the classification of a sound fragment is reduced to the problem of image recognition. The waveform and spectrogram are used as a visual representation of the image. The computational experiment was done based on Radvess open dataset including 8 different emotions: "neutral", "calm", "happy," "sad," "angry," "scared", "disgust", "surprised". The best accuracy result was 64%, which was produced by a combination of “|spectrogram + convolution neural network VGG-11”