title: Artificial neural network-based channel selection and loudness mapping.
abstract: We present in this paper artificial neural network techniques for implementing loudness mapping and "smart" channel selection for cochlear implant systems. For loudness mapping, a multilayer perceptron (MLP) is trained to perform the mapping for each channel according to threshold and comfort levels. It is shown that good accuracy mapping can be performed by a very simple MLP architecture. For channel selection, we propose a neural network-based method that can make "smart" selection. We describe and report results for the case in which 6 channels are to be selected from 18. The neural network-based selection system is trained on a multispeaker labeled speech database and tested on a database of different speakers and spoken sentences. Compared with methods used by leading cochlear implant systems, our approach produces significantly better results, and it is easy to implement in the speech processor of the cochlear implant system.
authors.affiliation: Systems Engineering and Design Automation Laboratory, Sydney University Electrical Engineering, Australia.
authors.forename: R J
authors.initials: RJ
authors.lastname: Wang
authors.forename: M A
authors.initials: MA
authors.lastname: Jabri
mesh_terms: D003054:Cochlear Implants; D006801:Humans; D008144:Loudness Perception; D016571:Neural Networks, Computer; D011571:Psychoacoustics; D013067:Speech Perception