A time warping neural network
Evan G. Levine · 2002
A method is proposed to improve any temporal pattern recognition system by time warping each pattern before presentation to the recognition system. The time warping function for a pattern is generated by repeated local application of a neural network to sections of the pattern. The output of this neural network is the slope of the warping function, and the internal weight parameters are trained by a gradient descent learning rule which attempts to minimize the recognition system's error. Experimental results show that this method can improve recognition of vowel phonemes.