Experiments in Medical Translation Shared Task at WMT 2014

By Jian Zhang. 2014

5 citations recorded by the source corpus.

This paper describes Dublin City University’s (DCU) submission to the WMT 2014 Medical Summary task. We report our results on the test data set in the French to English translation direction. We also report statistics collected from the corpora used to train our translation system. We conducted our experiment on the Moses 1.0 phrase-based translation system framework. We performed a variety of experiments on translation models, reordering models, operation sequence model and language model. We also experimented with data selection and removal the length constraint for phrase-pair extraction.

Subfields: Artificial Intelligence, Molecular Biology, Natural Language Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Philipp Koehn
2. Lucia Specia
3. Ondrej Bojar
4. Qun Liu
5. Graham Neubig
6. Rico Sennrich
7. Matt Post
8. Barry Haddow

In Molecular Biology

1. Lucia Specia
2. Ergun Biçici
3. Ondrej Bojar
4. Philipp Koehn
5. Barry Haddow
6. Andy Way
7. Qun Liu
8. Christof Monz

In Natural Language Processing

1. Philipp Koehn
2. Lucia Specia
3. Ondrej Bojar
4. Ergun Biçici
5. Barry Haddow
6. Matt Post
7. Qun Liu
8. Rico Sennrich

Citations in the corpus

• Findings of the 2014 Workshop on Statistical Machine Translation (2014, background): “, 2014) DCU-S Dublin City University (Zhang et al., 2014) LIMSI Laboratoire dInformatique pour la Mecanique et les Sciences de lIngénieur (Pécheux et al.”
• Parallel FDA5 for Fast Deployment of Accurate Statistical Machine Translation Systems (2014, methodology): “FDA5 is also used for selecting the training set in the WMT14 medical translation task (Calixto et al., 2014) and the tuning set in the WMT14 German-English translation task (Li et al.”