Publikation

Hierarchical Hybrid Translation between English and German

Yu Chen, Andreas Eisele

In: Viggo Hansen , Francois Yvon (Hrsg.). Proceedings of the 14th Annual Conference of the European Association for Machine Translation. Annual Conference of the European Association for Machine Translation (EAMT-2010) May 27-28 St. Raphaël France Seiten 90-97 EAMT EAMT 5/2010.

Abstrakt

We present new results from a hybrid combination of rule-based machine translation (RBMT) with a variant of statistical machine translation (SMT) that supports hierarchical structures and is therefore able to preserve more of the linguistic structures obtained from the RBMT system than versions of SMT that operate on flat phrases alone. Having shown in (Chen and Eisele, 2010) for the first time that a tighter integration of hierachical MT systems from different paradigms leads to consistent improvements for translation from German to English in various experimental settings, the current paper generalizes the approach to translation from English to German, where we observe similar improvements. These findings indicate that hybrid combinations of MT paradigms can benefit from structural similarities in the underlying models, which makes us expect even stronger benefits from a tight integration of different approaches.

joshua-lucy.pdf (pdf, 132 KB )

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence