2019/06/10 by Aarne Talman, Umut Sulubacak, Talman, Aarne +13
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Text Readability and Simplification #Topic Modeling
paper · pdf · doi:10.48550/arxiv.1906.04040
openalex publication_date 2019/06/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this paper, we present the University of Helsinki submissions to the WMT\n2019 shared task on news translation in three language pairs: English-German,\nEnglish-Finnish and Finnish-English. This year, we focused first on cleaning\nand filtering the training data using multiple data-filtering approaches,\nresulting in much smaller and cleaner training sets. For English-German, we\ntrained both sentence-level transformer models and compared different\ndocument-level translation approaches. For Finnish-English and English-Finnish\nwe focused on different segmentation approaches, and we also included a\nrule-based system for English-Finnish.\n