@inproceedings{morchid-etal-2014-topic,
    title = "A topic-based approach for post-processing correction of automatic translations",
    author = "Morchid, Mohamed  and
      Huet, St{\'e}phane  and
      Dufour, Richard",
    editor = {Federico, Marcello  and
      St{\"u}ker, Sebastian  and
      Yvon, Fran{\c{c}}ois},
    booktitle = "Proceedings of the 11th International Workshop on Spoken Language Translation: Evaluation Campaign",
    month = dec # " 4-5",
    year = "2014",
    address = "Lake Tahoe, California",
    url = "https://preview.aclanthology.org/fix-sig-urls/2014.iwslt-evaluation.10/",
    pages = "80--85",
    abstract = "We present the LIA systems for the machine translation evaluation campaign of the International Workshop on Spoken Language Translation (IWSLT) 2014 for the English-to-Slovene and English-to-Polish translation tasks. The proposed approach takes into account word context; first, it maps sentences into a latent Dirichlet allocation (LDA) topic space, then it chooses from this space words that are thematically and grammatically close to mistranslated words. This original post-processing approach is compared with a factored translation system built with MOSES. While this postprocessing method does not allow us to achieve better results than a state-of-the-art system, this should be an interesting way to explore, for example by adding this topic space information at an early stage in the translation process."
}