Year: 2010
Type: conference-paper
Abstract: In this paper we describe the statistical machine translation system of the RWTH Aachen University developed for the translation task of the Fifth Workshop on Statistical Machine Translation.Stateof-the-art phrase-based and hierarchical statistical MT systems are augmented with appropriate morpho-syntactic enhancements, as well as alternative phrase training methods and extended lexicon models.For some tasks, a system combination of the best systems was used to generate a final hypothesis.We participated in the constrained condition of German-English and French-English in each translation direction.
Source: RWTH Publications (RWTH Aachen)
Authors: Heger, Carmen, Wuebker, Joern, Huck, Matthias, Leusch, Gregor, Mansour, Saab, Stein, Daniel, Ney, Hermann
Institution: RWTH Aachen University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6996432016