Year: 2025
Type: conference-paper
Abstract: Converging societal and technical factors have transformed language technologies into userfacing applications used by the general public across languages.Machine Translation (MT) has become a global tool, with cross-lingual services now also supported by dialogue systems powered by multilingual Large Language Models (LLMs).Widespread accessibility has extended MT's reach to a vast base of lay users, many with little to no expertise in the languages or the technology itself.And yet, the understanding of MT consumed by such a diverse group of users-their needs, experiences, and interactions with multilingual systemsremains limited.In our position paper, we first trace the evolution of MT user profiles, focusing on non-experts and how their engagement with technology may shift with the rise of LLMs.Building on an interdisciplinary body of work, we identify three factors-usability, trust, and literacy-that are central to shaping user interactions and must be addressed to align MT with user needs.By examining these dimensions, we provide insights to guide the progress of more user-centered MT.
Institution: Fondazione Bruno Kessler
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4416036307