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Auditory representations of speech sounds in a neural model: the role of peripheral processing

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1 Author(s)
Damper, R.I. ; Dept. of Electron. & Comput. Sci., Southampton Univ., UK

The categorization of speech sounds by the auditory system has been a subject of intense attention. In the author's previous work it has been established that a two-stage computational model can mimic important aspects of the speech categorization behavior of human and animal listeners. The first stage employs a biologically motivated `front-end' for modeling the peripheral auditory system, and the second stage is a trainable artificial neural network `back-end' for modeling more central processes. The behavior is emergent in that it was not explicitly programmed into the model. A software model can be interrogated to find out the contribution of its component parts to the overall behavior. Replacing the auditory front-end by a more prosaic fast Fourier transform analyzer allows one to focus on the contribution of the acoustic in auditory transformation to categorization. We find that the front-end processor is not essential to category formation but plays an important part in the boundary-movement phenomenon, by emphasizing important time frequency of the speech signal

Published in:

Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on  (Volume:3 )

Date of Conference:

4-9 May 1998

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