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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Autors principals:	You Wang, Ming Zhang, RuMeng Wu, Han Gao, Meng Yang, Zhiyuan Luo, Guang Li
Format:	Artigo
Idioma:	Inglês
Publicat:	MDPI AG 2020-07-01
Col·lecció:	Brain Sciences
Matèries:	silent speech decoding neuromuscular signal spectrogram features Xception bidirectional long short-term memory
Accés en línia:	https://www.mdpi.com/2076-3425/10/7/442
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