Perceptive, non-linear speech processing and spiking neural networks
| Venue: | in G. Chollet et al. (Eds.) Nonlinear Speech Modeling, LNAI 3445 |
| Citations: | 2 - 0 self |
BibTeX
@INPROCEEDINGS{Rouat_perceptive,non-linear,
author = {Jean Rouat and Ramin Pichevar and Stéphane Loiselle and Université De Sherbrooke},
title = {Perceptive, non-linear speech processing and spiking neural networks},
booktitle = {in G. Chollet et al. (Eds.) Nonlinear Speech Modeling, LNAI 3445},
year = {},
pages = {317--337}
}
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Abstract
Abstract. Source separation and speech recognition are very difficult in the context of noisy and corrupted speech. Most conventional techniques need huge databases to estimate speech (or noise) density probabilities to perform separation or recognition. We discuss the potential of perceptive speech analysis and processing in combination with biologically plausible neural networks processors. We illustrate the potential of such non-linear processing of speech on two applications. The first is a source separation system inspired by Auditory Scene Analysis paradigm and the second is a crude spoken digit recogniser. We present preliminary results and discuss them.
