The University of Edinburgh-Uppsala University's Submission to the WMT 2020 Chat Translation Task

Nikita Moghe, Christian Hardmeier, Rachel Bawden

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

Abstract

This paper describes the joint submission of the University of Edinburgh and Uppsala University to the WMT’20 chat translation task for both language directions (English↔German). We use existing state-of-the-art machine translation models trained on news data and fine-tune them on in-domain and pseudo-indomain web crawled data. We also experiment with (i) adaptation using speaker and domain tags and (ii) using different types and amounts
of preceding context. We observe that contrarily to expectations, exploiting context degrades the results (and on analysis the data is not highly contextual). However using domain tags does improve scores according to the automatic evaluation. Our final primary systems use domain tags and are ensembles of
4 models, with noisy channel reranking of outputs. Our en-de system was ranked second in the shared task while our de-en system outperformed all the other system
Original languageEnglish
Title of host publication5th Conference on Machine Translation, WMT 2020 - Proceedings
Number of pages6
Publication date2020
Pages473-478
ISBN (Print)9781948087810
Publication statusPublished - 2020
Externally publishedYes

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