Silent Speech Decoding Using Spectrogram Features Based on Neuromuscular Activities

Silent speech decoding is a novel application of the Brain–Computer Interface (BCI) based on articulatory neuromuscular activities, reducing difficulties in data acquirement and processing. In this paper, spatial features and decoders that can be used to recognize the neuromuscular signals are inves...

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Detalles Bibliográficos

Principais autores:	You Wang, Ming Zhang, RuMeng Wu, Han Gao, Meng Yang, Zhiyuan Luo, Guang Li
Formato:	Artigo
Idioma:	Inglês
Publicado:	MDPI AG 2020-07-01
Series:	Brain Sciences
Assuntos:	silent speech decoding neuromuscular signal spectrogram features Xception bidirectional long short-term memory
Acceso en liña:	https://www.mdpi.com/2076-3425/10/7/442
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