Impacts of Cortical Regions on EEG-based Classification of Lexical Tones and Vowels in Spoken Speech

Mingtao Li1; Sio Hang Pun1; Fei Chen2

10.1109/EMBC40787.2023.10340428

2023

45th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)

2375-7477

1558-4615

979-8-3503-2448-8

2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

1-4

24-27 July 2023

Sydney, Australia

345 E 47TH ST, NEW YORK, NY 10017 USA

IEEE

Speech impairment is one of the most serious problems for patients with communication disorders, e.g., stroke survivors. The brain-computer interface (BCI) systems have shown the potential to alternatively control or rehabilitate the neurological damages in speech production. The effects of different cortical regions in speech-based BCI systems are essential to be studied, which are favorable for improving the performance of speech-based BCI systems. This work aimed to explore the impacts of different speech-related cortical regions in the electroencephalogram (EEG) based classification of seventy spoken Mandarin monosyllables carrying four vowels and four lexical tones. Seven audible speech production-related cortical regions were studied, involving Broca's and Wernicke's areas, auditory cortex, motor cortex, prefrontal cortex, sensory cortex, left brain, right brain, and whole brain. Following the previous studies in which EEG signals were collected from ten subjects during Mandarin speech production, the features of EEG signals were extracted by the Riemannian manifold method, and a linear discriminant analysis (LDA) was regarded as a classifier to classify different vowels and lexical tones. The results showed that when using electrodes from whole brain, the classifier reached the best performances, which were 48.5% for lexical tones and 70.0% for vowels, respectively. The vowel classification results under Broca's and Wernicke's areas, auditory cortex, or prefrontal cortex were higher than those under the motor cortex or sensory cortex. No such differences were observed in the lexical tone classification task.

Manifolds Electrodes Production Stroke (medical condition) Feature extraction Electroencephalography Brain-computer interfaces

其他

英语

EI ; CPCI-S

National Natural Science Foundation of China[61971212]

Computer Science ; Engineering

Computer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications ; Engineering, Biomedical

WOS:001133788302015

20240215361269

Brain ; Computer control systems ; Discriminant analysis ; Electroencephalography ; Interfaces (computer) ; Linguistics ; Speech communication

Biomedical Engineering:461.1 ; Medicine and Pharmacology:461.6 ; Computer Peripheral Equipment:722.2 ; Computer Applications:723.5 ; Control Systems:731.1 ; Speech:751.5 ; Information Sources and Analysis:903.1 ; Statistical Methods:922

IEEE

1.State Key Laboratory of Analog and Mixed-Signal VLSI, University of Macau, Taipa, Macau, China
2.Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China

Mingtao Li,Sio Hang Pun,Fei Chen. Impacts of Cortical Regions on EEG-based Classification of Lexical Tones and Vowels in Spoken Speech[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2023:1-4.