Md Raihan Khan

Md Raihan Khan

Lecturer in EEE (North Western University) & B.Sc. graduate (KUET). Efficient, geometry-aware deep learning: generative modeling, optimal transport, and neural signals.

Recognition of Bengali Vowels from Auditory Evoked Potentials Using CNN

Published in IEEE International Conference on Signal Processing, Information, Communication and Systems (SPICSCON), 2024 — Best Paper Award, 2024

This work explores auditory evoked potentials (AEP) as a modality for recognizing Bengali vowels from EEG recordings. Using the first EEG AEP dataset for imagined Bengali language tasks — collected with a low-cost OpenBCI acquisition system — a convolutional neural network is trained to classify vowel stimuli.

The proposed model demonstrates that robust vowel recognition is feasible from non-invasive EEG, contributing to language-specific brain–computer interface systems. The paper received the IEEE Best Paper Award.

Recommended citation: Tithi Das, Md Raihan Khan, and Md Mahbub Hasan, "Recognition of Bengali Vowels from Auditory Evoked Potentials Using CNN," IEEE SPICSCON 2024 (Best Paper Award).
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