A novel approach to hearing-aid signal processing is described, which attempts to re-establish a normal neural representation in the sensorineural impaired auditory system. Most hearing-aid fitting procedures are based on heuristics or some initial qualitative theory. These theories, such as loudness normalization, loudness equalization or maximal intelligibility can give vastly different results for a given individual, and each may provide variable results for different hearing impaired individuals with the same audiogram. Recent research in characterizing sensorineural hearing loss has delineated the importance of hair cell damage in understanding the bulk of sensorineural hearing impairments. A novel methodology based on restoring normal neural representation after the sensorineural impairment is presented here. This approach can be used for designing hearing-aid signal processing algorithms, as well as providing a general, automated means of predicting the relative intelligibility of a given speech sample in normal hearing and hearing impaired subjects.
['Jeff Bondy', 'Suzanna Becker', 'Ian C. Bruce', 'Laurel J. Trainor', 'Simon Haykin']
A novel signal-processing strategy for hearing-aid design: neurocompensation