mlsanityData to 13 Oct 2026

FAME-MT Dataset: Formality Awareness Made Easy for Machine Translation Purposes

arXiv 2405.11942 ↗First posted 20 May 2024cs.CLcited by 1

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Abstract (arXiv)

People use language for various purposes. Apart from sharing information, individuals may use it to express emotions or to show respect for another person. In this paper, we focus on the formality level of machine-generated translations and present FAME-MT -- a dataset consisting of 11.2 million translations between 15 European source languages and 8 European target languages classified to formal and informal classes according to target sentence formality. This dataset can be used to fine-tune machine translation models to ensure a given formality level for each European target language considered. We describe the dataset creation procedure, the analysis of the dataset's quality showing that FAME-MT is a reliable source of language register information, and we present a publicly available proof-of-concept machine translation model that uses the dataset to steer the formality level of the translation. Currently, it is the largest dataset of formality annotations, with examples expressed in 112 European language pairs. The dataset is published online: https://github.com/laniqo-public/fame-mt/ .

Key facts. Cited by 1 paper in the map (data through 13 Oct 2026). Builds on 21 of its 38 references that are in the map. First posted on arXiv 20 May 2024.

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21 of 38 references.

References · 21

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9 more
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  1. 2025Unlocking Latent Discourse Translation in LLMs Through Quality-Aware Decodingcited by 0