A topic-based approach for post-processing correction of automatic translations

Mohamed Morchid, Stéphane Huet, Richard Dufour


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.
Anthology ID:
2014.iwslt-evaluation.10
Volume:
Proceedings of the 11th International Workshop on Spoken Language Translation: Evaluation Campaign
Month:
December 4-5
Year:
2014
Address:
Lake Tahoe, California
Venue:
IWSLT
SIG:
Publisher:
Note:
Pages:
80–85
Language:
URL:
https://aclanthology.org/2014.iwslt-evaluation.10
DOI:
Bibkey:
Cite (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.
Cite (Informal):
A topic-based approach for post-processing correction of automatic translations (Morchid et al., IWSLT 2014)
Copy Citation:
PDF:
https://preview.aclanthology.org/update-css-js/2014.iwslt-evaluation.10.pdf