Recognition of Mentally Pronounced Russian Phonemes Using Convolutional Neural Networks and Electroencephalography Data-Reference-Cited by-同舟云学术

Recognition of Mentally Pronounced Russian Phonemes Using Convolutional Neural Networks and Electroencephalography Data

Published:2023-06 Issue:2 Volume:32 Page:73-85
ISSN:1060-992X
Container-title:Optical Memory and Neural Networks
language:en
Short-container-title:Opt. Mem. Neural Networks

Author:

Seleznyev L. E.,Chupakhin A. A.,Kostenko V. A.,Shevchenko A. O.,Vartanov A. V.

Publisher

Allerton Press

Subject

Electrical and Electronic Engineering,General Computer Science,Electronic, Optical and Magnetic Materials

Link

https://link.springer.com/content/pdf/10.3103/S1060992X23020066.pdf

Reference16 articles.

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3. Guo, G., Wang, H., Bell, D. A., Bi, Y., and Greer, K., An kNN model-based approach and its application in text categorization, in Computational Linguistics and Intelligent Text Processing Lecture Notes in Computer Science, 2004, pp. 559–570.

4. Gavrilenko, Y.V., Saada, D., Ilyushin, E., Vartanov, A.V., and Shevchenko, A.O., The electroencephalogram based classification of internally pronounced phonemes, Adv. Intell. Syst. Comput., 2020, vol. 1310, pp. 97–105.

5. Theodoros, E., Support vector machines: Theory and applications, Machine Learning and Its Applications, Advanced Lectures, 2001, pp. 249–257.

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