# The University of Helsinki submissions to the WMT19 news translation task

arXiv: https://arxiv.org/abs/1906.04040 · HTML: https://mlsanity.com/paper/1906.04040/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Jun 2019.

## Built on by (most cited first, 2 of 2)

- [The Great Misalignment Problem in Human Evaluation of NLP Methods](https://mlsanity.com/paper/2104.05361/) (2021)
- [Improving Long Context Document-Level Machine Translation](https://mlsanity.com/paper/2306.05183/) (2023)

## Abstract (arXiv)

In this paper, we present the University of Helsinki submissions to the WMT 2019 shared task on news translation in three language pairs: English-German, English-Finnish and Finnish-English. This year, we focused first on cleaning and filtering the training data using multiple data-filtering approaches, resulting in much smaller and cleaner training sets. For English-German, we trained both sentence-level transformer models and compared different document-level translation approaches. For Finnish-English and English-Finnish we focused on different segmentation approaches, and we also included a rule-based system for English-Finnish.