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A research project that explores the potential of DL models in detecting ERP (p300) in EEG signals. From EDA to modeling, we developed an end-to-end training and evaluation workflow that achieved an accuracy of 98% on the EPFL dataset. We utilized the achieved results in building a Neurophone and using the famous EMOTIV headset for EEG measurement.