Abstract
This article describes the Aalto University entry to the English-to-Finnish shared translation task in WMT 2015. The system participates in the constrained condition, but in addition we impose some further constraints, using no language-specific resources beyond those provided in the task. We use a morphological segmenter, Morfessor FlatCat, but train and tune it in an unsupervised manner. The system could thus be used for another language pair with a morphologically complex target language, without needing modification or additional resources.
Cite
CITATION STYLE
Grönroos, S. A., Virpioja, S., & Kurimo, M. (2015). Tuning phrase-based segmented translation for a morphologically complex target language. In 10th Workshop on Statistical Machine Translation, WMT 2015 at the 2015 Conference on Empirical Methods in Natural Language Processing, EMNLP 2015 - Proceedings (pp. 105–111). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w15-3010
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