Processing of acoustic signals in a cochlear model incorporating laterally coupled suppressive elements

Development of hearing machines with brain-like performance can be approached by faithfully modeling the human auditory nervous system. As an initial step in this effort, a composite cochlear model has been built which processes acoustic signals in a manner consistent with physiological responses recorded from the mammalian auditory nerve. The model integrates a current state of knowledge about cochlear function and provides a coherent picture of the representation of acoustic signals in the pattern of neural impulses distributed across a tonotopically organized array of auditory-nerve fibers. The model explicitly represents the active electromechanical responses of outer hair cells as a possible mechanism for adaptive control of basilar membrane damping, and introduces lateral coupling of resistive elements in the cochlear mechanics based on this mechanism. The output of the model is represented as an acoustic image being transferred to the central auditory nervous system in a massively parallel fashion over the auditory nerve. The impact of the cochlear nonlinearity on this image is explored. Experiments on applying this model to speech analysis show advantages of the cochlear modeling approach over traditional linear analysis methods.