DCU Terminology Translation System for Medical Query Subtask at WMT14
By Tsuyoshi Okita, Ali Hosseinzadeh Vahid, Andy Way, Qun Liu. 2014
5 citations recorded by the source corpus.
This paper describes the Dublin City University terminology translation system used for our participation in the query translation subtask in the medical translation task in the Workshop on Statistical Machine Translation (WMT14). We deployed six different kinds of terminology extraction methods, and participated in three different tasks: FR‐EN and EN‐ FR query tasks, and the CLIR task. We obtained 36.2 BLEU points absolute for FR‐EN and 28.8 BLEU points absolute for EN‐FR tasks where we obtained the first place in both tasks. We obtained 51.8 BLEU points absolute for the CLIR task.
Subfields: Artificial Intelligence, Molecular Biology, Natural Language Processing
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In Artificial Intelligence
- Philipp Koehn
- Ondrej Bojar
- Lucia Specia
- Graham Neubig
- Matt Post
- Barry Haddow
- Rico Sennrich
- Christof Monz
In Molecular Biology
- Lucia Specia
- Ondrej Bojar
- Philipp Koehn
- Barry Haddow
- Christof Monz
- Matt Post
- Yvette Graham
- Varvara Logacheva
In Natural Language Processing
- Philipp Koehn
- Lucia Specia
- Ondrej Bojar
- Barry Haddow
- Matt Post
- Christof Monz
- Rico Sennrich
- Graham Neubig
Citations in the corpus
- Findings of the 2014 Workshop on Statistical Machine Translation (2014, background): “, 2014) DCU-Q Dublin City University (Okita et al., 2014) DCU-S Dublin City University (Zhang et al.”
- DCU-Lingo24 Participation in WMT 2014 Hindi-English Translation task (2014, unknown): “The same technique is used in (Okita et al., 2014).”