EEG-based Classification of Imaginary Mandarin Tones

Zhang，Xinyu1; Li，Hua1; Chen，Fei2

10.1109/EMBC44109.2020.9176608

2020-07-01

1557-170X

978-1-7281-1991-5

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

2020-July

3889-3892

20-24 July 2020

Montreal, QC, Canada

Speech imagery based brain-computer interface (BCI) has the potential to assist patients with communication disorders to recover their speech communication abilities. Mandarin is a tonal language, and its tones play an important role in language perception and semantic understanding. This work studied the electroencephalogram (EEG) based classification of Mandarin tones based on speech imagery, and also compared the classification performance of speech imagery based BCIs at two test conditions with visual-only and combined audio-visual stimuli, respectively. Participants imagined 4 Mandarin tones at each condition. Common spatial patterns were applied to extract feature vectors, and support vector machine was used to classify different Mandarin tones from EEG data. Experimental results showed that the tonal articulation imagination task achieved a higher classification accuracy at the combined audio-visual condition (i.e., 80.1%) than at the visual-only condition (i.e., 67.7%). The results in this work supported that Mandarin tone information could be decoded from EEG data recorded in a speech imagery task, particularly under the combined audio-visual condition.

其他

英语

EI

20203809208161

Support vector machines ; Brain computer interface ; Image classification ; Semantics ; Speech communication

Medicine and Pharmacology:461.6 ; Computer Peripheral Equipment:722.2 ; Computer Software, Data Handling and Applications:723 ; Data Processing and Image Processing:723.2 ; Speech:751.5

2-s2.0-85091012478

Scopus

1.Shenzhen University,Health Science Center School of Biomedical Engineering,Shenzhen,China
2.Southern University of Science and Technology,Department of Electrical and Electronic Engineering,Shenzhen,China

Zhang，Xinyu,Li，Hua,Chen，Fei. EEG-based Classification of Imaginary Mandarin Tones[C],2020:3889-3892.