A Novel Channel Selection System in Cochlear Implants Using Artificial Neural Network
Abstract
State-of-the-art speech processors in cochlear implants perform channel selection using a spectral maxima strategy. This strategy can lead to confusions when high frequency features are needed to discriminate between sounds. We present in this paper a novel channel selection strategy based upon pattern recognition which al(cid:173) lows "smart" channel selections to be made. The proposed strategy is implemented using multi-layer perceptrons trained on a multi(cid:173) speaker labelled speech database. The input to the network are the energy coefficients of N energy channels. The output of the system are the indices of the M selected channels. We compare the performance of our proposed system to that of spectral maxima strategy, and show that our strategy can produce significantly better results.
Cite
Text
Jabri and Wang. "A Novel Channel Selection System in Cochlear Implants Using Artificial Neural Network." Neural Information Processing Systems, 1995.Markdown
[Jabri and Wang. "A Novel Channel Selection System in Cochlear Implants Using Artificial Neural Network." Neural Information Processing Systems, 1995.](https://mlanthology.org/neurips/1995/jabri1995neurips-novel/)BibTeX
@inproceedings{jabri1995neurips-novel,
title = {{A Novel Channel Selection System in Cochlear Implants Using Artificial Neural Network}},
author = {Jabri, Marwan A. and Wang, Raymond J.},
booktitle = {Neural Information Processing Systems},
year = {1995},
pages = {910-916},
url = {https://mlanthology.org/neurips/1995/jabri1995neurips-novel/}
}