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Nonlinear, biophysically-informed speech pathology detection

Abstract:

This paper reports a simple nonlinear approach to online acoustic speech pathology detection for automatic screening purposes. Straight-forward linear preprocessing followed by two nonlinear measures, based parsimoniously upon the biophysics of speech production, combined with subsequent linear classification, achieves an overall normal/pathological detection performance of 91.4%, and over 99% with rejection of 15% ambiguous cases. This compares favourably with more complex, computationally i...

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Volume:
2
Host title:
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Publication date:
2006-01-01
ISSN:
1520-6149
Source identifiers:
318904
ISBN-10:
142440469X
ISBN-13:
9781424404698
Pubs id:
pubs:318904
UUID:
uuid:e356007e-6de2-4de9-a260-653fd6cb4481
Local pid:
pubs:318904
Deposit date:
2013-11-17

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