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What is the real uptake of AI Interpreting?
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…
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What Lies Beyond Meta and Translated’s Advances in Supporting Low-Resource Languages
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…
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InterpretBank ASR 3.0 – Some thoughts from behind the scenes
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.…
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The Day the German Chancellor Said AI will Replace Interpreters in the EU
When asked recently about Spain’s request to make Catalan, Basque and Galician official languages of the European Union, German Chancellor Friedrich Merz offered a confident answer: “I believe that even in the medium term there is a very good solution: one day, thanks to artificial intelligence, we will no longer…
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Why the Next Big Wave of Speech Innovation May Be Hyperlocal
In the fast-moving world of artificial intelligence, speech translation is often portrayed as a race already won by a handful of global titans. Meta, Google, Microsoft, Zoom, and a few others have built astonishing systems capable of turning speech from one language into another almost instantly. Around them, a constellation…
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Giving AI Interpreters Eyes: Why Visual Grounding Matters
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…
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Beyond Conferences: Unlocking the Potential of AI in Public Service Interpreting
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…
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2025: The Year Machine Interpreting Went Mainstream
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…
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What is a Super-Human AI interpreter?
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…