Phonetic features extraction using time-delay neural networks

A.Waibel introduced Time-Delay Neural Networks (TDNNs) as a specific neural network architecture that is especially well adapted to the “dynamic nature of speech”. We propose here to use low-dimensioned TDNNs for discriminating between phonetic features. We give evaluations of the different performances and we comment them. We also compare direct phoneme recognition scores using a sophisticated classical classifier to those obtained with a medium-size TDNN.