Following two preceding WMT Shared Task on Parallel Corpus Filtering (Koehn et al., 2018,
2019), we posed again the challenge of assigning sentence-level quality scores for very …

We posed the shared task of assigning sentence-level quality scores for a very noisy corpus
of sentence pairs crawled from the web, with the goal of sub-selecting 1% and 10% of high …

Abstract Following the WMT 2018 Shared Task on Parallel Corpus Filtering, we posed the
challenge of assigning sentence-level quality scores for very noisy corpora of sentence pairs …

Abstract This paper describes Prompsit Language Engineering's submissions to the WMT
2018 parallel corpus filtering shared task. Our four submissions were based on an automatic …

Web-crawled data provides a good source of parallel corpora for training machine
translation models. It is automatically obtained, but extremely noisy, and recent work shows …

We present our semantic textual similarity approach in filtering a noisy web crawled parallel
corpus using YiSi—a novel semantic machine translation evaluation metric. The systems …

This paper introduces OpusFilter, a flexible and modular toolbox for filtering parallel corpora.
It implements a number of components based on heuristic filters, language identification …

This paper describes the Microsoft submission to the WMT2018 news translation shared
task. We participated in one language direction--English-German. Our system follows …

Despite being the seventh most widely spoken language in the world, Bengali has received
much less attention in machine translation literature due to being low in resources. Most …

When parallel or comparable corpora are harvested from the web, there is typically a
tradeoff between the size and quality of the data. In order to improve quality, corpus …