Morphological Segmentation and OPUS for Finnish-English Machine Translation
By Jörg Tiedemann, Filip Ginter, Jenna Kanerva. 2015
8 citations recorded by the source corpus.
This paper describes baseline systems for Finnish-English and English-Finnish machine translation using standard phrasebased and factored models including morphological features. We experiment with compound splitting and morphological segmentation and study the effect of adding noisy out-of-domain data to the parallel and the monolingual training data. Our results stress the importance of training data and demonstrate the effectiveness of morphological pre-processing of Finnish.
How researchers see this paper
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- Sara Stymne
- Fabienne Cap
- Jenna Kanerva
- Filip Ginter
- Jörg Tiedemann
- Robert Östling
- Marion Weller-Di Marco
- Philipp Koehn
Citations in the corpus
- Phrase-Based SMT for Finnish with More Data, Better Models and Alternative Alignment and Translation Tools (2016, methodology): “Sim-394 ilar to Tiedemann et al. (2015b), we introduce place-holder prepositions at the beginning of noun phrases bearing the corresponding case-marker in order to support word alignment.”