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arXiv · 0804.3269

Phoneme recognition in TIMIT with BLSTM-CTC

Santiago Fernández·Alex Graves·Juergen Schmidhuber
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Abstract

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.

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Santiago Fernández, Alex Graves, Juergen Schmidhuber. 2008-04-21. Phoneme recognition in TIMIT with BLSTM-CTC. https://arxiv.org/abs/0804.3269

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