---
title: "Findings of the WMT 2017 Biomedical Translation — Yepes 2017"
description: "This second edition of the WMT biomedical translation shared task looks at how well machine translation systems handle health and life-science texts…"
authors: ["Antonio Jimeno Yepes", "Aurélie Névéol", "Mariana Neves", "Karin Verspoor", "Ondřej Bojar", "Arthur Boyer", "Cristian Grozea", "Barry Haddow", "Madeleine Kittner", "Yvonne Lichtblau", "Pavel Pecina", "Roland Roller", "Rudolf Rosa", "Amy Siu", "Philippe Thomas", "Saskia Trescher"]
year: 2017
venue: "Proceedings of the Second Conference on Machine Translation"
source: "https://aclanthology.org/W17-4719/"
doi: "10.18653/v1/w17-4719"
licence: "CC BY 4.0 (ACL Anthology)"
licence_url: "https://creativecommons.org/licenses/by/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/papers/yepes-2017-findings-wmt-2017-biomedical-translation/"
---
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# Findings of the WMT 2017 Biomedical Translation Shared Task

**Authors:** [Antonio Jimeno Yepes](https://md.research.elamur.ai/free/authors/antonio-jimeno-yepes/), [Aurélie Névéol](https://md.research.elamur.ai/free/authors/aurelie-neveol/), [Mariana Neves](https://md.research.elamur.ai/free/authors/mariana-neves/), [Karin Verspoor](https://md.research.elamur.ai/free/authors/karin-verspoor/), [Ondřej Bojar](https://md.research.elamur.ai/free/authors/ondrej-bojar/), Arthur Boyer, [Cristian Grozea](https://md.research.elamur.ai/free/authors/cristian-grozea/), [Barry Haddow](https://md.research.elamur.ai/free/authors/barry-haddow/), [Madeleine Kittner](https://md.research.elamur.ai/free/authors/madeleine-kittner/), Yvonne Lichtblau, [Pavel Pecina](https://md.research.elamur.ai/free/authors/pavel-pecina/), Roland Roller et al. (16 authors) · **Year:** 2017 · **Venue:** Proceedings of the Second Conference on Machine Translation · **Licence:** [CC BY 4.0 (ACL Anthology)](https://creativecommons.org/licenses/by/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/W17-4719/) · [PDF](https://aclanthology.org/W17-4719.pdf) · [DOI 10.18653/v1/w17-4719](https://doi.org/10.18653/v1/w17-4719) · [OpenAlex](https://openalex.org/W2758685863)

**Citations:** 38 citations (openalex-snapshot · 2026-10-14) · [31](#cited-by) in our library, of the 140673 papers whose bibliographies we read

## Summary
This second edition of the WMT biomedical translation shared task looks at how well machine translation systems handle health and life-science texts between English and other European languages. Such translation can help clinicians and the public read medical content in their own language and help researchers write in English. The task grew from three to ten languages: cs, de, en, fr, hu, pl, pt, es, ro and sv. Systems translated from English into every other language, and from French, Spanish and Portuguese into English.

The organizers built new test sets from four sources:
- **Scielo and EDP Sciences:** titles and abstracts of scientific articles.
- **Cochrane and NHS:** health documents translated by experts, supplied through the KConnect and HimL projects.

Seven teams sent 82 runs, using both phrase-based SMT and neural MT, often with domain adaptation. Runs were scored with BLEU and judged manually by native speakers. Performance and translation quality rose compared with 2016. Manual judgments mostly matched BLEU rankings, which suggests automatic scores are informative for this domain.

## Key points
- **Test sets:** Cochrane (25 documents / 467 sentences) and NHS (25 documents / 1044 sentences) each cover eight target languages. Scielo serves the es/pt–en pairs, and EDP replaces it for en/fr.
- **Alignment quality:** about 88% of Scielo sentences (aligned with GMA) and 94% of EDP sentences (aligned with YASA) were correct on manually checked samples.
- **Teams:** Hunter, kyoto, Lilt, LMU, PJIIT, uedin-nmt and UHH, from five countries. Each team could submit up to three runs per pair and test set, within 10 days.
- **Notable BLEU results:** on Scielo, UHH clearly beat the simple baseline. On EDP en2fr, only kyoto outperformed the stronger LIMSI Moses baseline.
- **Limitations and errors:**
  - Test sets are small, no significance tests were run, and each comparison was judged by a single expert.
  - Manual review found mistranslated technical terms; one example rendered "vasopressor" as its antonym in Romanian.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

Fields: [Linguistics & languages](https://md.research.elamur.ai/free/shelves/linguistics/) · [Machine translation](https://md.research.elamur.ai/free/shelves/machine-translation/)

Topics: [Machine translation](https://md.research.elamur.ai/free/topics/machine-translation/)

## Cited by

Cited by

31 papers of our library cite it (of the 140673 whose bibliographies we read); 1 of them have a page here, 30 not yet.

- [Findings of the 2017 Conference on Machine Translation (WMT17)](https://md.research.elamur.ai/free/papers/bojar-2017-findings-2017-conference-machine-translation/)

## Cite

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@inproceedings{yepes2017findings,
  title = {{Findings of the WMT 2017 Biomedical Translation Shared Task}},
  author = {Yepes, Antonio Jimeno and Névéol, Aurélie and Neves, Mariana and Verspoor, Karin and Bojar, Ondřej and Boyer, Arthur and Grozea, Cristian and Haddow, Barry and Kittner, Madeleine and Lichtblau, Yvonne and Pecina, Pavel and Roller, Roland and Rosa, Rudolf and Siu, Amy and Thomas, Philippe and Trescher, Saskia},
  booktitle = {Proceedings of the Second Conference on Machine Translation},
  year = {2017},
  doi = {10.18653/v1/w17-4719},
  url = {https://doi.org/10.18653/v1/w17-4719}
}
```

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## References

15 references, 2 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

1. Ondřej Bojar, Rajen Chatterjee, Christian Federmann, Yvette Graham, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, Varvara Logacheva, Christof Monz, Matteo Negri, Aurelie Neveol, Mariana Neves, Martin Popel, Matt Post, Raphael Rubino, Carolina Scarton, Lucia Specia, Marco Turchi,… [find](https://scholar.google.com/scholar?q=Ondr%CC%8Cej+Bojar%2C+Rajen+Chatterjee%2C+Christian+Federmann%2C+Yvette+Graham%2C+Barry+Haddow%2C+Matthias+Huck%2C+Antonio+Jimeno+Yepes%2C+Philipp+Koehn%2C+Varvara+Logacheva%2C+Christof+Monz%2C+Matteo+Negri%2C+Aurelie+Neveol%2C+M) [our card](https://md.research.elamur.ai/free/papers/bojar-2016-findings-2016-conference-machine-translation/)
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