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

Citation

Newton M & Smith L (2011) Biologically-inspired neural coding of sound onset for a musical sound classification task. In: The 2011 International Joint Conference on Neural Networks (IJCNN). The 2011 International Joint Conference on Neural Networks, San Jose, California USA, 31.07.2011-05.08.2011. San Jose, California: Institute of Electrical and Electronics Engineers (IEEE), pp. 1386-1393. https://doi.org/10.1109/IJCNN.2011.6033386

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 neuron alone.

Keywords
; Neural networks (Computer science); Music Physiological aspects

People

Professor Leslie Smith

Emeritus Professor, Computing Science