Work

Findings of the WMT 2021 Shared Task on Quality Estimation

Year: 2021

Type: other

Abstract: We report the results of the WMT 2021 shared task on Quality Estimation, where the challenge is to predict the quality of the output of neural machine translation systems at the word and sentence levels. This edition focused on two main novel additions: (i) prediction for unseen languages, i.e. zero-shot settings, and (ii) prediction of sentences with catastrophic errors. In addition, new data was released for a number of languages, especially post-edited data. Participating teams from 19 institutions submitted altogether 1263 systems to different task variants and language pairs.

Source: Underline Science Inc.

DOI: 10.48448/n1nv-gd47

Authors: Association for Computational Linguistics 2021, Blain, Frédéric, Chaudhary, Vishrav, Fomicheva, Marina, Li, Zhenhao, Martins, André, Specia, Lucia, Zerva, Chrysoula

Institutions: University of Wolverhampton, Meta (United Kingdom), Meta (United States), University of Sheffield, Imperial College London, Instituto de Telecomunicações

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W6891649707

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