A tonotopic artificial neural network architecture for phoneme probability estimation

A novel sparse ANN connection scheme is proposed. It is inspired by the so called tonotopic organization of the auditory nerve, and allows a more detailed representation of the speech spectrum to be input to an ANN than is commonly used. A consequence of the new connection scheme is that more resources are allocated to analysis within narrow frequency sub bands-a concept that has recently been investigated by others with so called sub band ASR. ANNs with the proposed architecture have been evaluated on the TIMIT database for phoneme recognition, and are found to give better phoneme recognition performance than ANNs based on standard mel frequency cepstrum input. The lowest achieved phone error rate, 26.7%, is very close to the lowest published result for the core test set of the TIMIT database