in All Things Localization

When it comes to translating software interfaces for users in different languages, machine translation (MT) is a well-established tool for scaling up linguists’ productivity, but what happens when a software product comes equipped with an engine ready to do its own translating? This week, Meta AI is breaking headlines with the claim it has delivered on its ambitions to create just that technology for its ecosystem, which it framed earlier this year as necessary to furnish a metaverse available to users from around the world in real time. After months of hype, that bold assertion has generated an outburst of enthusiasm from tech publications large and small thrilled to see the metaverse dream of a “universal speech translator” emerging in real live R&D color. But more to the point of where the news was truly heard, it is also making waves in language services, with publications in our realm like Slator eyeing Meta’s announcement for what it really strides toward: accurate, real-time machine translation capable of delivering meaning between languages as seamlessly as a professional interpreter. In short, the proverbial cold fusion of translation technology.   

Machine translation is imperfect and needs the work of human linguists to correct its mistakes and enhance its sound and feel. This is an axiom of virtually any modern MT-based localization workflow. Software-based scenarios make some of the best examples of why MT is not enough by itself, with robust needs for linguistic testing and functional testing to ensure that what makes sense linguistically in a software translation also fits the screen as good product for users. Beyond the challenges of localizing static interfaces, it is harder still to imagine two people speaking in their own languages, free of scripts or predictable behaviors, and understanding each other completely thanks only to an algorithm’s work of an instant. Meta has not yet achieved that, from this week’s reports, but it is getting closer, and leaving no question it intends to.

Related:  Language Preservation, Climate Action, and LLMs: How AI Translation is Driving Positive Change

Meanwhile, the specifics of the announcement are notable in their nuances, especially where progress remains to make. Instant translation between 200 languages equates to 40,000 language pairs, but not all of these are equally fluent links, as Meta AI notes in its remarks on the challenges of engaging lower-resourced languages that have relatively few speakers and minimal data for engines to train on. More broadly, Meta’s existing ecosystem of products surrounding Facebook seem to be the primary deployment for the model at the moment, suggesting it is a tool for in-housing the company’s vast needs for translation simply to exist as the product it aims to be, if not yet a universal translation tool.  While Meta may indeed be relaying more of its internally generated information to users across languages, it has yet to become a truly auto translating VR environment, leaving hope that for the time being, at least, the best practices of software translation remain in the purview of professional translation services.

To learn more about CSOFT’s technology-driven translation solutions in over 250 languages, please visit us at    

[dqr_code size="120" bgcolor="#fff"]