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Two Approaches to Correcting Homophone Confusions in a Hybrid Machine Translation System |
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Published in | Proceedings of the Second Workshop on Hybrid Approaches to Translation. Sofia (Bulgaria) - 8 Aug. 2013 - Association for Computational Linguistics. 2013, p. 109-116 | |
Abstract | In the context of a hybrid French-to-English SMT system for translating online forum posts, we present two methods for addressing the common problem of homophone confusions in colloquial written language. The first is based on hand-coded rules; the second on weighted graphs derived from a large-scale pronunciation resource, with weights trained from a small bicorpus of domain language. With automatic evaluation, the weighted graph method yields an improvement of about +0.63 BLEU points, while the rulebased method scores about the same as the baseline. On contrastive manual evaluation, both methods give highly significant improvements (p < 0.0001) and score about equally when compared against each other. | |
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Research group | TIM/ISSCO | |
Citation (ISO format) | BOUILLON, Pierrette et al. Two Approaches to Correcting Homophone Confusions in a Hybrid Machine Translation System. In: Proceedings of the Second Workshop on Hybrid Approaches to Translation. Sofia (Bulgaria). [s.l.] : Association for Computational Linguistics, 2013. p. 109-116. https://archive-ouverte.unige.ch/unige:30954 |