Authors
Hasim Sak, Oriol Vinyals, Georg Heigold, Andrew Senior, Erik McDermott, Rajat Monga, Mark Mao
Publication date
2014
Journal
entropy
Volume
15
Issue
16
Pages
17-18
Description
Abstract We recently showed that Long Short-Term Memory (LSTM) recurrent neural
networks (RNNs) outperform state-of-the-art deep neural networks (DNNs) for large scale
acoustic modeling where the models were trained with the cross-entropy (CE) criterion. It
has also been shown that sequence discriminative training of DNNs initially trained with the
CE criterion gives significant improvements. In this paper, we investigate sequence
discriminative training of LSTM RNNs in a large scale acoustic modeling task. We train the ...
networks (RNNs) outperform state-of-the-art deep neural networks (DNNs) for large scale
acoustic modeling where the models were trained with the cross-entropy (CE) criterion. It
has also been shown that sequence discriminative training of DNNs initially trained with the
CE criterion gives significant improvements. In this paper, we investigate sequence
discriminative training of LSTM RNNs in a large scale acoustic modeling task. We train the ...
Total citations
Scholar articles
H Sak, O Vinyals, G Heigold, A Senior, E McDermott… - 2014
Dates and citation counts are estimated and are determined automatically by a computer program.