Silent Speech Decoding Using Spectrogram Features Based on Neuromuscular Activities

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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Bibliographic Details
Main Authors: You Wang, Ming Zhang, RuMeng Wu, Han Gao, Meng Yang, Zhiyuan Luo, Guang Li
Format: Article
Language:English
Published: MDPI AG 2020-07-01
Series:Brain Sciences
Subjects:
silent speech decoding
neuromuscular signal
spectrogram features
Xception
bidirectional long short-term memory
Online Access:https://www.mdpi.com/2076-3425/10/7/442

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https://www.mdpi.com/2076-3425/10/7/442

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