Papers with WMT 2020 shared task

2 papers
Data Filtering using Cross-Lingual Word Embeddings (2021.naacl-main)

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Challenge: varying task definitions and data conditions make it difficult to draw a meaningful comparison.
Approach: They propose to use language identification to perform data filtering on MT data based on cross-lingual word embeddings to identify weaknesses in language identification tool.
Outcome: The proposed methods perform well on three real-life, high resource MT tasks while performing weakly within more realistic task conditions.
Experts, Errors, and Context: A Large-Scale Study of Human Evaluation for Machine Translation (2021.tacl-1)

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Challenge: a large study of machine translation systems shows poor evaluation procedures can lead to erroneous conclusions.
Approach: They propose an evaluation methodology grounded in explicit error analysis based on the Multidimensional Quality Metrics framework.
Outcome: The proposed evaluation methodology outperforms crowd workers in two languages . it shows that human-based metrics outperformed crowd workers .

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