Abstract
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.
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Balaguer-Ballester, E., Bouchachia, A., Jiang, B., Denham, S.L. (2012). Neurodynamical Top-Down Processing during Auditory Attention. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7664. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34481-7_33
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DOI: https://doi.org/10.1007/978-3-642-34481-7_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-34480-0
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