Understanding the neural dynamics underlying the fast discrimination of music and speech in noise is a very challenging task for neurocomputational and speech recognition models. In this paper, we present a model of interacting neural ensembles which includes a top-down modulation of the peripheral system dynamics, based on bottom-up perceptual predictions. This bi-directional processing could enable the detection of sudden changes in the input sounds in noise; advancing in the understanding of how listeners can improve their perception by focusing their attention. Our preliminary work opens the possibility of developing a pioneering class of neurophysiological-based speech processors for cochlear implants and speech recognition devices under degraded conditions. © 2012 Springer-Verlag.
CITATION STYLE
Balaguer-Ballester, E., Bouchachia, A., Jiang, B., & Denham, S. L. (2012). Neurodynamical top-down processing during auditory attention. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7664 LNCS, pp. 266–273). https://doi.org/10.1007/978-3-642-34481-7_33
Mendeley helps you to discover research relevant for your work.