Phoneme recognition using an auditory model and a recurrent self-organizing neural network
T.R. Anderson · 1992
Neural networks that use unsupervised learning were used on the output of a neurophysiologically based model of the auditory periphery to perform phoneme recognition. Experiments which compared the performance of a recurrent self-organizing feature map to that of the standard Kohonen self-organizing feature map show that the recurrent version performs significantly better (t-test, p>