title: A cocktail party with a cortical twist: how cortical mechanisms contribute to sound segregation.
abstract: Sound systems and speech technologies can benefit greatly from a deeper understanding of how the auditory system, and particularly the auditory cortex, is able to parse complex acoustic scenes into meaningful auditory objects and streams under adverse conditions. In the current work, a biologically plausible model of this process is presented, where the role of cortical mechanisms in organizing complex auditory scenes is explored. The model consists of two stages: (i) a feature analysis stage that maps the acoustic input into a multidimensional cortical representation and (ii) an integrative stage that recursively builds up expectations of how streams evolve over time and reconciles its predictions with the incoming sensory input by sorting it into different clusters. This approach yields a robust computational scheme for speaker separation under conditions of speech or music interference. The model can also emulate the archetypal streaming percepts of tonal stimuli that have long been tested in human subjects. The implications of this model are discussed with respect to the physiological correlates of streaming in the cortex as well as the role of attention and other top-down influences in guiding sound organization.
authors.affiliation: Department of Electrical and Computer Engineering, Johns Hopkins University, Barton, Baltimore, Maryland 21218, USA. mounya@jhu.edu
authors.forename: Mounya
authors.initials: M
authors.lastname: Elhilali
authors.forename: Shihab A
authors.initials: SA
authors.lastname: Shamma
mesh_terms: D000161:Acoustic Stimulation; D001288:Attention; D001303:Auditory Cortex / Q000502:physiology*; D001307:Auditory Perception; D016000:Cluster Analysis; D003198:Computer Simulation; D006801:Humans; D008954:Models, Biological; D009146:Music; D009622:Noise; D010363:Pattern Recognition, Automated; D046709:Pattern Recognition, Physiological; D010470:Perceptual Masking; D010898:Pitch Perception; D013018:Sound Spectrography; D013067:Speech Perception; D013997:Time Factors