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        <title>A topic-based approach for post-processing correction of automatic translations</title>
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        <namePart type="given">Mohamed</namePart>
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        <namePart type="given">Stéphane</namePart>
        <namePart type="family">Huet</namePart>
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    <name type="personal">
        <namePart type="given">Richard</namePart>
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            <title>Proceedings of the 11th International Workshop on Spoken Language Translation: Evaluation Campaign</title>
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            <namePart type="given">Marcello</namePart>
            <namePart type="family">Federico</namePart>
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        <name type="personal">
            <namePart type="given">Sebastian</namePart>
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        <name type="personal">
            <namePart type="given">François</namePart>
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    <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.</abstract>
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%0 Conference Proceedings
%T A topic-based approach for post-processing correction of automatic translations
%A Morchid, Mohamed
%A Huet, Stéphane
%A Dufour, Richard
%Y Federico, Marcello
%Y Stüker, Sebastian
%Y Yvon, François
%S Proceedings of the 11th International Workshop on Spoken Language Translation: Evaluation Campaign
%D 2014
%8 dec 4 5
%C Lake Tahoe, California
%F morchid-etal-2014-topic
%X 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.
%U https://aclanthology.org/2014.iwslt-evaluation.10
%P 80-85

Markdown (Informal)

[A topic-based approach for post-processing correction of automatic translations](https://aclanthology.org/2014.iwslt-evaluation.10) (Morchid et al., IWSLT 2014)

• A topic-based approach for post-processing correction of automatic translations (Morchid et al., IWSLT 2014)

ACL

• Mohamed Morchid, Stéphane Huet, and Richard Dufour. 2014. A topic-based approach for post-processing correction of automatic translations. In Proceedings of the 11th International Workshop on Spoken Language Translation: Evaluation Campaign, pages 80–85, Lake Tahoe, California.