Identifying Hearing Deficiencies from Statistically Learned Speech Features for Personalized Tuning of Cochlear Implants
Published: Apr 1, 2015
Abstract
Cochlear implants (CIs) are an effective intervention for individuals with severe-to-profound sensorineural hearing loss. Currently, no tuning procedure exists that can fully exploit the technology. We propose online unsupervised algorithms to learn features from the speech of a severely-to-profoundly hearing-impaired patient round-the-clock and compare the features to those learned from the normal hearing population using a set of...
Paper Details
Title
Identifying Hearing Deficiencies from Statistically Learned Speech Features for Personalized Tuning of Cochlear Implants
Published Date
Apr 1, 2015
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