A comparison of auditory models for speaker independent phoneme recognition
Timothy R. Anderson · IEEE International Conference on Acoustics Speech and Signal Processing · 1993
Neural networks that employ unsupervised learning were used on the output of two different models of the auditory periphery to perform phoneme recognition. Experiments which compared the performance of these two auditory model representations with that of mel-cepstral coefficients show that the auditory models perform significantly better (T-test, P>