  We compare the performance of a recurrent neural network with the best
results published so far on phoneme recognition in the TIMIT database. These
published results have been obtained with a combination of classifiers.
However, in this paper we apply a single recurrent neural network to the same
task. Our recurrent neural network attains an error rate of 24.6%. This result
is not significantly different from that obtained by the other best methods,
but they rely on a combination of classifiers for achieving comparable
performance.
