Publikation

Multi-Engine Machine Translation with an Open-Source (SMT) Decoder

Yu Chen, Andreas Eisele, Christian Federmann, Eva Hasler, Michael Jellinghaus, Silke Theison

In: Proceedings of the Second Workshop on Statistical Machine Translation. Workshop on Statistical Machine Translation (WMT) Seiten 193-196 2007.

Abstrakt

We describe an architecture that allows to combine statistical machine translation(SMT) with rule-based machine translation(RBMT) in a multi-engine setup. We use a variant of standard SMT technology to align translations from one or more RBMT systems with the source text. We incorporate phrases extracted from these alignments into the phrase table of the SMT system and use the open-source decoder Moses to find good combinations of phrases from SMT training data with the phrases derived from RBMT. First experiments based on this hybrid architecture achieve promising results.

Weitere Links

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence