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In this paper, we propose a novel neu-ral network model called RNN Encoder– Decoder that consists of two recurrent neural networks (RNN). One RNN encodes a sequence of symbols into a fixed-length vector representation, and the other decodes the representation into another sequence of symbols. The encoder and de-coder of the proposed model are jointly(More)
This paper describes an open-source implementation of the so-called continuous space language model and its application to statistical machine translation. The underlying idea of this approach is to attack the data sparseness problem by performing the language model probability estimation in a continuous space. The projection of the words and the(More)
This paper describes the three systems developed by the LIUM for the IWSLT 2011 evaluation campaign. We participated in three of the proposed tasks, namely the Automatic Speech Recognition task (ASR), the ASR system combination task (ASR_SC) and the Spoken Language Translation task (SLT), since these tasks are all related to speech translation. We present(More)
This paper proposes a new phone lattice based method for automatic language recognition from speech data. By using phone lattices some approximations usually made by language identification (LID) systems relying on phonotactic constraints to simplify the training and decoding processes can be avoided. We demonstrate the use of phone lattices both in(More)
Language models play an important role in large vocabulary speech recognition and statistical machine translation systems. The dominant approach since several decades are back-off language models. Some years ago, there was a clear tendency to build huge language models trained on hundreds of billions of words. Lately, this tendency has changed and recent(More)
" Boosting " is a general method for improving the performance of any weak learning algorithm that consistently generates classifiers which need to perform only slightly better than random guessing. A recently proposed and very promising boosting algorithm is AdaBoost [4]. It has been applied with great success to several benchmark machine learning problems(More)
This paper describes the development of several machine translation systems for the 2009 WMT shared task evaluation. We only consider the translation between French and English. We describe a statistical system based on the Moses de-coder and a statistical post-editing system using SYSTRAN's rule-based system. We also investigated techniques to(More)