Natalia Segal


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SYSTRAN Purely Neural MT Engines for WMT2017
Yongchao Deng | Jungi Kim | Guillaume Klein | Catherine Kobus | Natalia Segal | Christophe Servan | Bo Wang | Dakun Zhang | Josep Crego | Jean Senellart
Proceedings of the Second Conference on Machine Translation


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LIMSI English-French speech translation system
Natalia Segal | Hélène Bonneau-Maynard | Quoc Khanh Do | Alexandre Allauzen | Jean-Luc Gauvain | Lori Lamel | François Yvon
Proceedings of the 11th International Workshop on Spoken Language Translation: Evaluation Campaign

This paper documents the systems developed by LIMSI for the IWSLT 2014 speech translation task (English→French). The main objective of this participation was twofold: adapting different components of the ASR baseline system to the peculiarities of TED talks and improving the machine translation quality on the automatic speech recognition output data. For the latter task, various techniques have been considered: punctuation and number normalization, adaptation to ASR errors, as well as the use of structured output layer neural network models for speech data.

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Traduire la parole: le cas des TED Talks [Speech translation: the TED Talks case study]
Natalia Segal | Hélène Bonneau-Maynard | François Yvon
Traitement Automatique des Langues, Volume 55, Numéro 2 : Traitement automatique du langage parlé [Spoken language processing]


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A corpus of post-edited translations (Un corpus d’erreurs de traduction) [in French]
Guillaume Wisniewski | Anil Kumar Singh | Natalia Segal | François Yvon
Proceedings of TALN 2013 (Volume 2: Short Papers)

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Design and Analysis of a Large Corpus of Post-Edited Translations: Quality Estimation, Failure Analysis and the Variability of Post-Edition
Guillaume Wisniewski | Anil Kumar Singh | Natalia Segal | François Yvon
Proceedings of Machine Translation Summit XIV: Papers