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Voice recognition, classification of emotions in speech using neural networks

Kovalchuk Veronika Viktorovna  (Moscow state University technical University. N. E. Bauman, Moscow)

Petrenko Elizaveta Olegovna  (candidate of technical Sciences, associate Professor, Moscow state technical University. N. E. Bauman, Moscow)

Machine learning Technologies in General are one of the most interesting and effective ways to solve voice recognition problems. Since the creation of the first computing machines, people have dreamed of creating a machine that will learn and solve problems. This dream led to the development of an entire field of science, now known as the science of artificial intelligence. the aim of the work is to study voice recognition, classification of emotions in speech using a neural network, understanding why this area is so interesting in our time. For further work the most actual methods of voice recognition through a neural network, methods of training of a neural network were studied. As a result, data were obtained on the methods on the basis of which neural networks can make any conclusions about the owner of the voice.

Keywords:artificial neural network (ins), classification and recognition of emotions, voice recognition, speech
 

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Citation link:
Kovalchuk V. V., Petrenko E. O. Voice recognition, classification of emotions in speech using neural networks // Современная наука: актуальные проблемы теории и практики. Серия: Естественные и Технические Науки. -2020. -№01. -С. 96-102
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