Abstract
In this paper, we address the problem of generating English tag questions (TQs) (e.g. it is, isn’t it?) in Machine Translation (MT). We propose a post-edition solution, formulating the problem as a multi-class classification task. We present (i) the automatic annotation of English TQs in a parallel corpus of subtitles and (ii) an approach using a series of classifiers to predict TQ forms, which we use to post-edit state-of-the-art MT outputs. Our method provides significant improvements in English TQ translation when translating from Czech, French and German, in turn improving the fluidity, naturalness, grammatical correctness and pragmatic coherence of MT output.
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CITATION STYLE
Bawden, R. (2017). Machine Translation, it’s a question of style, innit? The case of English tag questions. In EMNLP 2017 - Conference on Empirical Methods in Natural Language Processing, Proceedings (pp. 2507–2512). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/d17-1265
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