Combining Local and Document-Level Context: The LMU Munich Neural Machine Translation System at WMT19

Stojanovski, Dario und Fraser, Alexander (2019): Combining Local and Document-Level Context: The LMU Munich Neural Machine Translation System at WMT19. In: Fourth Conference on Machine Translation (Wmt 2019): S. 400-406

Abstract

We describe LMU Munich's machine translation system for English -> German translation which was used to participate in the WMT19 shared task on supervised news translation. We specifically participated in the document-level MT track. The system used as a primary submission is a context-aware Transformer capable of both rich modeling of limited contextual information and integration of large-scale document-level context with a less rich representation. We train this model by fine-tuning a big Transformer baseline. Our experimental results show that document-level context provides for large improvements in translation quality, and adding a rich representation of the previous sentence provides a small additional gain.

• Dokumententyp: Zeitschriftenartikel
• Fakultätsübergreifende Einrichtungen: Centrum für Informations- und Sprachverarbeitung (CIS)
• Themengebiete: 400 Sprache > 400 Sprache
• Sprache: Englisch