A new concept for Cochlear implant speech processing.
OBJECTIVE: A new speech processing concept and its implementation cochlear implant neural net, simulation and stimulation (CINSTIM), for cochlear implant systems is currently under investigation. The main objectives of this new strategy are to improve speech perception within the early rehabilitation period for prelingually deaf cochlear implant users and to improve speech perception in noise for all implant users. The advantage of this approach is the capability to assess and compare entirely different speech processing methods within the existing implant hardware. DESIGN: The processing concept is based on discrete sequences of distinguishable stimulus patterns, robust speech processing, and a classifier. The embedded Kohonen classifier employs unsupervised neural net algorithms. RESULTS: Initial experimental results have validated the general processing scheme as well as the development of this complex software. In addition, a limited alphabet of distinguishable stimulus patterns was achieved and assessed with experienced users of a conventional cochlear implant system. Test subjects were able to learn and recognize up to 60% of these artificial patterns after a few training sessions. Currently this speech processing strategy is being evaluated through the Cochlear MSP system; however, it is compatible with the other computer driven digital cochlear implant systems.