The RWTH Machine Translation System
نویسندگان
چکیده
We present the statistical machine translation system used by RWTH in the second TC-STAR evaluation. We give a short overview of the system as used in the first evaluation and then enumerate the improvements of the system over the last months. We then discuss the results obtained by our group in the evaluation.
منابع مشابه
The RWTH machine translation system for IWSLT 2007
The RWTH system for the IWSLT 2007 evaluation is a combination of several statistical machine translation systems. The combination includes Phrase-Based models, a n-gram translation model and a hierarchical phrase model. We describe the individual systems and the method that was used for combining the system outputs. Compared to our 2006 system, we newly introduce a hierarchical phrase-based tr...
متن کاملThe RWTH Aachen German-English Machine Translation System for WMT 2014
This paper describes the statistical machine translation (SMT) systems developed at RWTH Aachen University for the German→English translation task of the ACL 2014 Eighth Workshop on Statistical Machine Translation (WMT 2014). Both hierarchical and phrase-based SMT systems are applied employing hierarchical phrase reordering and word class language models. For the phrase-based system, we run dis...
متن کاملThe System Combination RWTH Aachen: SYSTRAN for the NTCIR-10 PatentMT Evaluation
This paper describes the joint submission by RWTH Aachen University and SYSTRAN in the Chinese-English Patent Machine Translation Task at the 10th NTCIR Workshop. We specify the statistical systems developed by RWTH Aachen University and the hybrid machine translation systems developed by SYSTRAN. We apply RWTH Aachen’s combination techniques to create consensus hypotheses from very different s...
متن کاملThe RWTH System Combination System for WMT 2009
RWTH participated in the System Combination task of the Fourth Workshop on Statistical Machine Translation (WMT 2009). Hypotheses from 9 German→English MT systems were combined into a consensus translation. This consensus translation scored 2.1% better in BLEU and 2.3% better in TER (abs.) than the best single system. In addition, cross-lingual output from 10 French, German, and Spanish→English...
متن کاملThe RWTH Aachen University English-German and German-English Machine Translation System for WMT 2017
This paper describes the statistical machine translation system developed at RWTH Aachen University for the English→German and German→English translation tasks of the EMNLP 2017 Second Conference on Machine Translation (WMT 2017). We use ensembles of attention-based neural machine translation system for both directions. We use the provided parallel and synthetic data to train the models. In add...
متن کامل