The RWTH Aachen machine translation systems for IWSLT 2013
Joern Wuebker, Stephan Peitz, Tamer Alkhouli, Jan-Thorsten Peter, Minwei Feng, Markus Freitag, Hermann Ney
Abstract
This work describes the statistical machine translation (SMT) systems of RWTH Aachen University developed for the evaluation campaign International Workshop on Spoken Language Translation (IWSLT) 2013. We participated in the English→French, English↔German, Arabic→English, Chinese→English and Slovenian↔English MT tracks and the English→French and English→German SLT tracks. We apply phrase-based and hierarchical SMT decoders, which are augmented by state-of-the-art extensions. The novel techniques we experimentally evaluate include discriminative phrase training, a continuous space language model, a hierarchical reordering model, a word class language model, domain adaptation via data selection and system combination of standard and reverse order models. By application of these methods we can show considerable improvements over the respective baseline systems.- Anthology ID:
- 2013.iwslt-evaluation.10
- Volume:
- Proceedings of the 10th International Workshop on Spoken Language Translation: Evaluation Campaign
- Month:
- December 5-6
- Year:
- 2013
- Address:
- Heidelberg, Germany
- Venue:
- IWSLT
- SIG:
- SIGSLT
- Publisher:
- Note:
- Pages:
- Language:
- URL:
- https://aclanthology.org/2013.iwslt-evaluation.10
- DOI:
- Cite (ACL):
- Joern Wuebker, Stephan Peitz, Tamer Alkhouli, Jan-Thorsten Peter, Minwei Feng, Markus Freitag, and Hermann Ney. 2013. The RWTH Aachen machine translation systems for IWSLT 2013. In Proceedings of the 10th International Workshop on Spoken Language Translation: Evaluation Campaign, Heidelberg, Germany.
- Cite (Informal):
- The RWTH Aachen machine translation systems for IWSLT 2013 (Wuebker et al., IWSLT 2013)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2013.iwslt-evaluation.10.pdf