Findings of the WMT Shared Task on Machine Translation Using Terminologies

Abstract

Language domains that require very careful use of terminology are abundant and reflect a significant part of the translation industry. In this work we introduce a benchmark for evaluating the quality and consistency of terminology translation, focusing on the medical (and COVID-19 specifically) domain for five language pairs: English to French, Chinese, Russian, and Korean, as well as Czech to German. We report the descriptions and results of the participating systems, commenting on the need for further research efforts towards both more adequate handling of terminologies as well as towards a proper formulation and evaluation of the task.

Publication
Proceedings of the 6th Conference on Machine Translation (WMT21)
Md Mahfuz Ibn Alam
Md Mahfuz Ibn Alam
PhD Student

I work on robustness

Antonios Anastasopoulos
Antonios Anastasopoulos
Assistant Professor

I work on multilingual models, machine translation, speech recognition, and NLP for under-served languages.

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