  This article describes the Aalto University entry to the WMT18 News
Translation Shared Task. We participate in the multilingual subtrack with a
system trained under the constrained condition to translate from English to
both Finnish and Estonian. The system is based on the Transformer model. We
focus on improving the consistency of morphological segmentation for words that
are similar orthographically, semantically, and distributionally; such words
include etymological cognates, loan words, and proper names. For this, we
introduce Cognate Morfessor, a multilingual variant of the Morfessor method. We
show that our approach improves the translation quality particularly for
Estonian, which has less resources for training the translation model.
