Findings of the WMT 2019 Shared Task on Parallel Corpus Filtering for Low-Resource Conditions

August 23, 2019

Abstract

Following the WMT 2018 Shared Task on Parallel Corpus Filtering (Koehn et al., 2018), we posed the challenge of assigning sentencelevel quality scores for very noisy corpora of sentence pairs crawled from the web, with the goal of sub-selecting 2% and 10% of the highest-quality data to be used to train machine translation systems. This year, the task tackled the low resource condition of Nepali– English and Sinhala–English. Eleven participants from companies, national research labs, and universities participated in this task.

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AUTHORS

Written by

Vishrav Chaudhary

Juan Pino

Paco Guzmán

Philipp Koehn

Publisher

WMT ACL

Research Topics

Speech & Audio

Natural Language Processing (NLP)

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