Deliverable 5.3 Machine translation quality evaluation and post-editing for minoritised languages

Machine translation quality evaluation and post-editing for minoritised languages.

By Dr. Federico Gaspari and Dr. Catalina Amengual Ripoll, Adapt Centre, Dublin City University.

In this presentation Dr. Gaspari (DCU) offers an overview of good practices to maximize the benefits of using machine translation (MT) in appropriate situations, while avoiding potential risks. Taking into account the latest advancements due to AI, especially with regard to minoritised languages, the session explained the main advantages and challenges of automatic and human/manual approaches to the evaluation of MT quality. This provided the basis to illustrate effective post-editing strategies, when MT output is corrected and improved with human intervention.

PDF of the presentation:

D5.3 Federico Gaspari Catalina Amengual FOSTERLANG EHU 28 5 2026 compressed (5)

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University of Warsaw
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Center for Research and Practice in Cultural Continuity
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FOSTERLANG: “Fostering Linguistic Capital: A Roadmap for Reversing the Diversity Crisis and Activating Societal Benefits in Europe”, Grant Agreement No. 101178387, Horizon Europe (HORIZON)."