In a June 19, 2024 paper, researchers from the University of Sheffield, the University of Waterloo, the University of Manchester, the University of International Business and Economics (UIBE), and the tech company 01.AI introduced a multilingual dataset for evaluating machine translation (MT) quality of metaphorical language.

This new dataset aims to fill a gap in MT evaluation by focusing on the complexities of translating metaphors, where the intended meaning differs from the literal interpretation.

Metaphorical expressions pose significant challenges for MT systems because their meaning extends beyond individual words. As the researchers highlighted, “metaphor translation is more challenging than literal translation.” 

Despite the fact that “metaphorical expressions are widely used in daily life for communication and vivid description,” the challenge of accurately machine translating them remains largely unaddressed due to resource scarcity and difficulties in handling the variation in linguistic forms and cultural norms inherent in metaphors.

Source: https://slator.com/

Full article: https://slator.com/new-dataset-for-evaluating-metaphorical-language-in-machine-translation/