## Smooth Bilingual N-gram Translation

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Citations: | 2 - 1 self |

### BibTeX

@MISC{Schwenk_smoothbilingual,

author = {Holger Schwenk and Marta R. Costa-jussà and José A. R. Fonollosa},

title = {Smooth Bilingual N-gram Translation},

year = {}

}

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### Abstract

We address the problem of smoothing translation probabilities in a bilingual N-grambased statistical machine translation system. It is proposed to project the bilingual tuples onto a continuous space and to estimate the translation probabilities in this representation. A neural network is used to perform the projection and the probability estimation. Smoothing probabilities is most important for tasks with a limited amount of training material. We consider here the BTEC task of the 2006 IWSLT evaluation. Improvements in all official automatic measures are reported when translating from Italian to English. Using a continuous space model for the translation model and the target language model, an improvement of 1.5 BLEU on the test data is observed. 1

### Citations

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- 2007
(Show Context)
Citation Context ...In particular, the problem of generalization to new translations seems to be promising to us. This could be addressed by the so-called factored phrase-based model as implemented in the Moses decoder (=-=Koehn et al., 2007-=-). In this approach words are decomposed into several factors. These factors are trans437 lated and a target phrase is generated. This model could be complemented by a factored continuous tuple N-gram... |

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Continuous space language models,” Computer Speech and Language
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Citation Context ...ingful interpolations even when only a limited amount of training material is available. This approach was successfully applied to language modeling in large vocabulary continuous speech recognition (=-=Schwenk, 2007-=-) and to language modeling in phrase-based SMT systems (Schwenk et al., 2006). In this paper, we investigate whether this approach is useful to smooth the probabilities involved in the bilingual tuple... |

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Citation Context ...e is generated. This model could be complemented by a factored continuous tuple N-gram. Factored word language models were already successfully used in speech recognition (Bilmes and Kirchhoff, 2003; =-=Alexandrescu and Kirchhoff, 2006-=-) and an extension to machine translation seems to be promising. The described smoothing method was explicitly developed to tackle the data sparseness problem in tasks like the BTEC corpus. It is well... |

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Factored language models and generalized backoff
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Citation Context ...437 lated and a target phrase is generated. This model could be complemented by a factored continuous tuple N-gram. Factored word language models were already successfully used in speech recognition (=-=Bilmes and Kirchhoff, 2003-=-; Alexandrescu and Kirchhoff, 2006) and an extension to machine translation seems to be promising. The described smoothing method was explicitly developed to tackle the data sparseness problem in task... |

1 |
Statistical phrased-based machine translation
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Citation Context ...w years, the use of context in SMT systems has provided great improvements in translation. SMT has evolved from the original word-based approach to phrase-based translation systems (Och et al., 1999; =-=Koehn et al., 2003-=-). A phrase is defined as a group of source words ˜ f that should be translated together into a group of target words ˜e. The translation model in phrase-based systems includes the phrase translation ... |

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Citation Context ...C) as used in the 2006 evaluations of the international workshop on spoken language translation (IWSLT). This corpus consists of typical sentences from phrase books for tourists in several languages (=-=Takezawa et al., 2002-=-). We report results on the supplied development corpus of 489 sentences and the official test set of the IWSLT’06 evaluation. The main measure is the BLEU score, using seven reference translations. T... |