Human EEG and Recurrent Neural Networks Exhibit Common Temporal Dynamics During Speech Recognition

Recent deep-learning artificial neural networks have shown remarkable success in recognizing natural human speech, however the reasons for their success are not entirely understood. Success of these methods might be because state-of-the-art networks use recurrent layers or dilated convolutional laye...

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Detalles Bibliográficos
Autores principales: Hashemnia, Saeedeh, Grasse, Lukas, Soni, Shweta, Tata, Matthew S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8296978/
https://www.ncbi.nlm.nih.gov/pubmed/34305540
http://dx.doi.org/10.3389/fnsys.2021.617605

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8296978/
https://www.ncbi.nlm.nih.gov/pubmed/34305540
http://dx.doi.org/10.3389/fnsys.2021.617605

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