Word-level language modeling for P300 spellers based on discriminative graphical models.

Journal: Journal of neural engineering
Published Date:

Abstract

OBJECTIVE: In this work we propose a probabilistic graphical model framework that uses language priors at the level of words as a mechanism to increase the performance of P300-based spellers.

Authors

  • Jaime F Delgado Saa
    Signal Proc. Info. Syst. Lab, Sabanci University, Istanbul, Turkey. Robotics & Intelligent Syst. Lab, Universidad del Norte, Barranquilla, Colombia.
  • Adriana de Pesters
  • Dennis McFarland
  • Müjdat Çetin