WMT 2013 8 th Workshop on Statistical Machine Translation
نویسندگان
چکیده
منابع مشابه
TÜBİTAK - BİLGEM German - English Machine Translation Systems for WMT ’ 13
This paper describes TÜBİTAK-BİLGEM statistical machine translation (SMT) systems submitted to the Eighth Workshop on Statistical Machine Translation (WMT) shared translation task for German-English language pair in both directions. We implement phrase-based SMT systems with standard parameters. We present the results of using a big tuning data and the effect of averaging tuning weights of diff...
متن کاملTÜBİTAK-BİLGEM German-English Machine Translation Systems for W13
This paper describes TÜBİTAK-BİLGEM statistical machine translation (SMT) systems submitted to the Eighth Workshop on Statistical Machine Translation (WMT) shared translation task for German-English language pair in both directions. We implement phrase-based SMT systems with standard parameters. We present the results of using a big tuning data and the effect of averaging tuning weights of diff...
متن کاملThe RWTH Aachen Machine Translation System for WMT 2013
This paper describes the statistical machine translation (SMT) systems developed at RWTH Aachen University for the translation task of the ACL 2013 Eighth Workshop on Statistical Machine Translation (WMT 2013). We participated in the evaluation campaign for the French-English and German-English language pairs in both translation directions. Both hierarchical and phrase-based SMT systems are app...
متن کاملJoint WMT 2013 Submission of the QUAERO Project
This paper describes the joint submission of the QUAERO project for the German→English translation task of the ACL 2013 Eighth Workshop on Statistical Machine Translation (WMT 2013). The submission was a system combination of the output of four different translation systems provided by RWTH Aachen University, Karlsruhe Institute of Technology (KIT), LIMSI-CNRS and SYSTRAN Software, Inc. The tra...
متن کاملThe RWTH System Combination System for WMT 2010
RWTH participated in the System Combination task of the Fifth Workshop on Statistical Machine Translation (WMT 2010). For 7 of the 8 language pairs, we combine 5 to 13 systems into a single consensus translation, using additional n-best reranking techniques in two of these language pairs. Depending on the language pair, improvements versus the best single system are in the range of +0.5 and +1....
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2013