Biologically-inspired neural coding of sound onset for a musical sound classification task

Abstract

A biologically-inspired neural coding scheme for the early auditory system is outlined. The cochlea response is simulated with a passive gammatone filterbank. The output of each bandpass filter is spike-encoded using a zero-crossing based method over a range of sensitivity levels. The scheme is inspired by the highly parallellised nature of the auditory nerve innervation within the cochlea. A key aspect of early auditory processing is simulated, namely that of onset detection, using leaky integrate-and-fire neuron models. Finally, a time-domain neural network (the echo state network) is used to tackle the what task of auditory perception using the output of the onset detection neurons alone. A set of interim results are presented.

DOI: 10.1109/IJCNN.2011.6033386

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@article{Newton2011BiologicallyinspiredNC, title={Biologically-inspired neural coding of sound onset for a musical sound classification task}, author={Michael J. Newton and Leslie S. Smith}, journal={The 2011 International Joint Conference on Neural Networks}, year={2011}, pages={1386-1393} }