ABSTRACT
Auditory segmentation is critical for complex auditory pattern processing. We present a neural network framework for auditory pattern segmentation. The network consists of laterally coupled two-dimensional neural oscillators with a global inhibitor. One dimension represents time and another one represents frequency. We show that this architecture can in real time group auditory features into a segment by phase synchrony and segregate different segments by desynchronization. The network demonstrates a set of psychological phenomena regarding primitive auditory stream segregation. The neuroplausibility and possible extensions of the model are discussed.
