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The architecture of the emotion recognition program by speech segments.

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Τίτλος: The architecture of the emotion recognition program by speech segments.
Συγγραφείς: Tsaregorodtsev, A.V.1 (AUTHOR), Samoylov, V.E.1 (AUTHOR), Zenov, A.E.1 (AUTHOR), Zelenina, A.N.2 (AUTHOR), Petrosov, D.A.3 (AUTHOR), Pleshakova, E.S.3 (AUTHOR), Osipov, A.V.3 (AUTHOR), Ivanov, M.N.3 (AUTHOR), Petrosova, N.V.4 (AUTHOR), Lopatnuk, L.A.5 (AUTHOR), Radygin, V.Y.6 (AUTHOR) vyradygin@mephi.ru, Roga, S.N.7 (AUTHOR)
Πηγή: Procedia Computer Science. 2022, Vol. 213, p338-345. 8p.
Θεματικοί όροι: Emotion recognition, Speech perception, Automatic speech recognition, Natural language processing, Image recognition (Computer vision), Machine learning
Περίληψη: The article discusses the issues of automatic recognition of the emotional coloring of a person's utterance using machine learning methods. In the software being developed, a change in the basic tone of a person's voice is taken as a basis. The architecture of the program is based on a multilayer perceptron. The result of the classifier is the choice of one of eight possible classes of emotions. In the course of the study, the accuracy of the classification of emotions was determined and the main directions of the development of the program were outlined. [ABSTRACT FROM AUTHOR]
Βάση Δεδομένων: Supplemental Index
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  – Url: https://www.doi.org/10.1016/j.procs.2022.11.076?
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: The architecture of the emotion recognition program by speech segments.
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  Data: <searchLink fieldCode="JN" term="%22Procedia+Computer+Science%22">Procedia Computer Science</searchLink>. 2022, Vol. 213, p338-345. 8p.
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  Data: The article discusses the issues of automatic recognition of the emotional coloring of a person's utterance using machine learning methods. In the software being developed, a change in the basic tone of a person's voice is taken as a basis. The architecture of the program is based on a multilayer perceptron. The result of the classifier is the choice of one of eight possible classes of emotions. In the course of the study, the accuracy of the classification of emotions was determined and the main directions of the development of the program were outlined. [ABSTRACT FROM AUTHOR]
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        Value: 10.1016/j.procs.2022.11.076
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