Исследования моделей распознавания звуков речи на основе нейронных сетей глубокого обучения для экспертизы цифровых фонограмм / Соловьев В. И., Рыбальский О. В., Журавель В. В., Семенова Н. В. (2021)
Ukrainian

English  Cybernetics and Systems Analysis   /     Issue (2021, 57 (1))

Solovyov V.I., Rybalskiy O.V., Zhuravel V.V., Semenova N.V.
Analyzing the models of speech recognition on the basis of neural networks of deep learning for examination of digital phonograms

The authors analyze the models based on deep learning neural networks on the basis of the general approach to pauses and speech signals as different types of audio information fixed in a phonogram, different in some characteristics. It is shown that such an approach allows generating the learning database with the use of the general for pauses and signals of speech methods of preliminary processing of information. This provides a higher level of unification of network learning methods intended for solution of various examination problems. © 2021, Springer Science+Business Media, LLC, part of Springer Nature.

Keywords: deep learning neural network, digital audio recording device, digital phonogram, digital treatment of phonograms, examination, learning database, Deep neural networks, E-learning, Learning systems, Neural networks, Speech communication, Speech recognition, Audio information, Learning database, Learning neural networks, Network learning, Preliminary processing, Speech signals, Deep learning


Cite:
Solovyov V.I., Rybalskiy O.V., Zhuravel V.V., Semenova N.V. (2021). Analyzing the models of speech recognition on the basis of neural networks of deep learning for examination of digital phonograms. Cybernetics and Systems Analysis, 57 (1), 153–159. doi: https://doi.org/10.1007/s10559-021-00336-y http://jnas.nbuv.gov.ua/article/UJRN-0001199864 [In Russian].


 

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