The University of Edinburgh-Uppsala University's Submission to the WMT 2020 Chat Translation Task
- Nikita Moghe,
- ,
- Rachel Bawden
- University of Edinburgh,
- Uppsala University
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-reviewOpen access
Publication Information
Output type
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-reviewOriginal language
EnglishPages from-to (Number of pages)
Pages 473-478 (6 pages)Publication milestones
- Published - 2020
Publication status
Published - 2020
ISBN (Print)
9781948087810Publication IDs
- ORCID: /0000-0002-6103-7275/work/156308167
- Scopus: 85112078784
Host publication title
5th Conference on Machine Translation, WMT 2020 - ProceedingsAbstract
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
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
Publication metrics
PlumX
Citations
8
Access to documents
Related Event
Title
Conference on Machine Translation
Event type
ConferenceDate
19/11/2020 - 20/11/2020Location
VIRTUAL
