| Titre | Amélioration a posteriori de la traduction automatique par métaheuristique |
| Type de publication | Thesis |
| Année de publication | 2016 |
| Auteurs | Lavoie-Courchesne, S. |
| Academic Department | Département d'informatique et de recherche opérationnelle |
| Degree | M.Sc. |
| Number of Pages | 75 |
| Date Published | 07/2016 |
| Endroit d'édition | Montréal |
| Mots-clés | Collocations, language model, Local search, Metaheuristic, Métaheuristique, Modèle de langue, Recherche locale, Statistical machine translation, Traduction automatique statistique |
| Résumé | Statistical Machine Translation is a field ingreat demand and where machines are still far from producing human-level results.The main method used is a segment by segment linear translation of a sentence, which prevents modification of already translated parts of the sentence. Research for this memoir is based on an approach used by Langlais, Patry and Gotti 2007, which tries to correct a completed translation by modifying segments following a function which needs to be optimized. As a first step, exploration of new traits such as an inverted language model and a collocation model brings a new dimension to the optimization function. As a second step, use of different metaheuristics, such as the greedy and randomized greedy algorithms, allows greater depth while exploring the search space and allows a greater improvement of the objective function. |
