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Proceedings Paper

Exploration of temporal processing of a sequential network for speech parameter estimation
Author(s): Haiyan Ye; Shengrui Wang; Gerard Bailly; Francois Robert
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Paper Abstract

In this paper, we present a study of temporal information processing using a recurrent network and speech data. The task of this neural network is the formant tracking of continuous speech, a classical but difficult problem in speech processing. For better analysis of the results, this task is divided into two sub-tasks: a qualitative task (formant presence detection) and a quantitative task (formant frequency calculation). The network performs quite well for the qualitative task (91% detection) but not as well for the quantitative task (65% of correct estimation). Future work direction is discussed and several questions raised at the end of the paper.

Paper Details

Date Published: 1 August 1990
PDF: 7 pages
Proc. SPIE 1294, Applications of Artificial Neural Networks, (1 August 1990); doi: 10.1117/12.21207
Show Author Affiliations
Haiyan Ye, ICP/Univ. Stendhal (France); (Switzerland)
Shengrui Wang, TIM3(France); (Canada)
Gerard Bailly, ICP/Univ. Stendhal (France)
Francois Robert, TIM3 (France)

Published in SPIE Proceedings Vol. 1294:
Applications of Artificial Neural Networks
Steven K. Rogers, Editor(s)

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