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Only a few years ago, end-to-end speech-to-speech translation (S2ST) seemed like one of those technologies that belonged to conference talks and research papers rather than real products. When Google introduced Translatotron in 2019, it was a glimpse of what might one day be possible: translating speech directly into speech, without detours through text, and even…

Last week, I moderated a webinar on AI Adoption in Interpreting Workflows, organised by GALA’s Special Interest Group Interpreting. The aim was modest but necessary: to look at how AI interpreting is actually being used today, and to invite an open discussion among practitioners and stakeholders. To do that, we brought together two viewpoints that…

Two recent announcements — Meta’s Omnilingual ASR and Translated’s Lara 200 Languages — remind us that progress in AI-driven language technology is far from plateauing. Together, they demonstrate how automatic speech recognition and large language models for translation tasks, the two core components of current machine interpreting systems, are being extended to an impressive range…

A few days ago, we finally released InterpretBank ASR 3.0. This version means a lot to me — not because it’s “new”, but because it feels right — or at least that’s my genuine feeling about it. It took a few years, and a few wrong turns, to get here. But I think the wait…

At this year’s AMTA 2025 conference, I presented some research on a simple but overlooked question: what happens when AI interpreters can not only listen, but also see? Today’s machine interpreting systems, i.e. a specific form of speech-to-speech translation for immediate use, work remarkably well. They can turn spoken sentences in one language into spoken…

When discussions about AI in interpreting arise, they almost always focus on conference interpreting: multilingual summits, corporate meetings, or international events. This focus is unsurprising: conference interpreting is highly visible and associated with prestige, as in the UN or the EU. Yet this emphasis has created a blind spot, both in the practical reality, but…

With Zoom, Apple, and Google jumping in, real-time translation is becoming as ordinary as Wi-Fi. Technologies rarely need to be perfect to change the world. They simply need to be everywhere. Smartphones, cloud storage, and video calls all followed this path: flawed at first, but once they became ubiquitous, their shortcomings mattered less than their…

Discussions about artificial intelligence (AI) in interpreting usually revolve around two scenarios: using AI to support human interpreters or developing machine interpreting systems capable of delivering acceptable results on their own. Many stakeholders still doubt whether AI interpreters are realistic at all, while others already accept them as an emerging reality. A smaller group has…

The idea of a machine that listens to speech in one language and instantly speaks it back in another — all in real time, and without missing a beat — has long captured the imagination of researchers, technologists, and organizations working in multilingual communication. This is the vision behind end-to-end machine interpreting: a single AI…