Paralinguistic model for emotions recognition with deep neural networks

In this paper the computer paralinguistic model for emotions recognition based on deep neural networks is proposed. The main stages of its construction were studied and relevant models of the deep convolutional networks and recurrent networks with LSTM memory cell were used. Intensive computer experiments on the emotions recognition from human speech with proposed model were conducted. As the data for research and testing of our model RAVDESS dataset of audio recordings was selected. The results showed a high efficiency of the explored model, and the accuracy estimates for some classes of emotions were reached 90%.

Авторы
Shchetinin E.Y.1 , Sevastianov L.A. 2, 3 , Kulyabov D.S. 2 , Ayrjan E.A. 3, 4 , Demidova A.V. 2
Издательство
Институт проблем управления им. В.А. Трапезникова РАН
Язык
Английский
Страницы
42-50
Статус
Опубликовано
Год
2020
Организации
  • 1 Financial University, Government of the Russian Federation
  • 2 Peoples' Friendship University of Russia (RUDN University)
  • 3 Joint Institute for Nuclear Research
  • 4 Dubna State University
Ключевые слова
emotions recognition; paralinguistic model; convolutional network; ResNet18; recurrent network; BLSTM model; RAVDESS
Цитировать
Поделиться

Другие записи

Shchetinin E.Y., Sevastianov L.A., Ayrjan E.A., Demidova A.V.
Распределенные компьютерные и телекоммуникационные сети: управление, вычисление, связь (DCCN-2020). Институт проблем управления им. В.А. Трапезникова РАН. 2020. С. 33-41
Houankpo H.G.K., Kozyrev D.V., Nibasumba E., Mouale M.N.B., Sergeeva I.A.
Распределенные компьютерные и телекоммуникационные сети: управление, вычисление, связь (DCCN-2020). Институт проблем управления им. В.А. Трапезникова РАН. 2020. С. 51-59