Extensions of recurrent neural network language model

We present several modifications of the original recurrent neural net work language model (RNN LM). While this model has been shown to significantly outperform many competitive language modeling techniques in terms of accuracy, the remaining problem is the computational complexity. In this work, we...

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Veröffentlicht in:	2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) S. 5528 - 5531
Hauptverfasser:	Mikolov, Tomas, Kombrink, Stefan, Burget, Lukas, Cernocky, Jan Honza, Khudanpur, Sanjeev
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.05.2011
Schlagworte:	Artificial neural networks Backpropagation Computational modeling language modeling Probability distribution Recurrent neural networks speech recognition Training Vocabulary
ISBN:	9781457705380, 1457705389
ISSN:	1520-6149
Online-Zugang:	Volltext
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