Hybrid Morphological Segmentation for Phrase-Based Machine Translation

By Stig-Arne Grönroos, Sami Virpioja, Mikko Kurimo. 2016

This article describes the Aalto University entry to the English-to-Finnish news translation shared task in WMT 2016. Our segmentation method combines the strengths of rule-based and unsupervised morphology. We also attempt to correct errors in the boundary markings by post-processing with a neural morph boundary predictor.

Citations in the corpus

• Findings of the 2016 Conference on Machine Translation (2016, neutral): “AALTO Aalto University (Grönroos et al., 2016)”