Can we identify the category of imagined phoneme from EEG

Panachakel, JT and Sharma, K and Anusha, AS and Ramakrishnan, AG (2021) Can we identify the category of imagined phoneme from EEG. In: 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2021, 1 - 5 November 2021, Virtual, Online, pp. 459-462.

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Abstract

Phonemes are classified into different categories based on the place and manner of articulation. We investigate the differences between the neural correlates of imagined nasal and bilabial consonants (distinct phonological categories). Mean phase coherence is used as a metric for measuring the phase synchronisation between pairs of electrodes in six cortical regions (auditory, motor, prefrontal, sensorimotor, so-matosensory and premotor) during the imagery of nasal and bilabial consonants. Statistically significant difference at 95% confidence interval is observed in beta and lower-gamma bands in various cortical regions. Our observations are inline with the directions into velocities of articulators and dual stream prediction models and support the hypothesis that phonological categories not only exist in articulated speech but can also be distinguished from the EEG of imagined speech.

Item Type:	Conference Paper
Publication:	Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Publisher:	Institute of Electrical and Electronics Engineers Inc.
Additional Information:	The copyright for this article belongs to Institute of Electrical and Electronics Engineers Inc.
Keywords:	Linguistics, Classifieds; Confidence interval; Cortical regions; Gamma band; Low-gamma; Neural correlate; Phase coherence; Phase synchronization; Sensorimotors; Statistically significant difference, Speech, electroencephalography; speech; speech perception, Electroencephalography; Speech; Speech Perception
Department/Centre:	Division of Electrical Sciences > Electrical Engineering
Date Deposited:	18 Apr 2023 10:01
Last Modified:	18 Apr 2023 10:01
URI:	https://eprints.iisc.ac.in/id/eprint/80633

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