Paper

USE OF NEURAL NETWORKS FOR THE RECOGNITION OF PLACE

The Boltzmann machine algorithm and Science, McGill the error back propagation algorithm were used to learn to recognize the place of articulation of vowels (front, center or back), represented by a static description of spectral lines. The error rate is shown to depend on the coding. Results are comparable or better than those obtained by us on the same data using Hidden Markov Models. We also show a fault tolerant property of the neural nets, i.e. that the error on the test set increases slowly and gradually when an increasing number of nodes fail.

Authors: Yoshua Bengio · Renato De Mori

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