TY - RPRT
T1 - Neural networks for nonlinear discriminant analysis in continuous speech recognition
T3 - Saarbrücken, 1996
A1 - Reichl,W.
A1 - Harengel,S.
A1 - Wolfertstetter,F.
A1 - Ruske,G.
Y1 - 2011/09/06
N2 - In this paper neural networks for Nonlinear Discriminant Analysis in continuous speech recognition are presented. Multilayer Perceptrons are used to estimate a-posteriori probabilities for Hidden-Markov Model states, which are the optimal discriminant features for the separation of the HMM states. The a-posteriori probabilities are transformed by a principal component analysis to calculate the new features for semicontinuous HMMs, which are trained by the known Maximum-Likelihood training. The nonlinear discriminant transformation is used in speaker-independent phoneme recognition experiments and compared to the standard Linear Discriminant Analysis technique.
KW - Künstliche Intelligenz
CY - Saarbrücken
PB - Saarländische Universitäts- und Landesbibliothek
AD - Postfach 151141, 66041 Saarbrücken
UR - http://scidok.sulb.uni-saarland.de/volltexte/2011/4193
ER -