A talent that speaks Hungarian

I’ve long coordinated transcription projects for a language services company based in Los Angeles. On earlier projects I only handled the Italian team, familiar ground. This time I was also given France and Hungary. So far, no problem: the languages change, the method doesn’t. Then, though, the Hungarians started disappearing.

How I ended up reviewing Hungarian transcripts without knowing a single word

The Hungarian contributors were unhappy with the rates, and to some extent they had a point. Despite doubling the pay and adding several bonuses, the team kept thinning out. The local contact was new to the role, unsure of herself and slow to decide. The result: transcript reviews landed on my desk, and I had never studied a word of Hungarian in my life. No background, no reference points, just a pile of audio files and text to check line by line.

The method born out of necessity

With no manual to follow, I built a three-step process of my own. Step one: listen to every audio file in full, start to finish, before even looking at the text. Step two: read the entire existing transcript and, with the help of artificial intelligence, reconstruct the context and topic of the conversation. Step three: check that every line met the client’s guidelines and segment the speech with surgical precision. At first it felt like an impossible task. How do you judge the quality of a text written in a language you’d never even heard of before that particular Monday morning?

A language’s rhythm comes through even without understanding it

And yet languages speak to me, even when their meaning stays out of reach. After about ten files I started to sense the rhythm of the sentences, recognize a few recurring words, and pick up on where one thought ended and another began. This isn’t wishful thinking: newborns can already tell their mother tongue apart from a foreign language based on sound patterns alone, as a classic study on language discrimination in the first days of life has shown. If a brain just days old can find its way through sound without a single word of vocabulary, an ear trained by years of work on texts can manage something similar, with a bit more patience.

Between sleepless nights and packed days, with help from another Italian linguist who knew just as little Hungarian as I did, we managed to fix the segmentation, the annotations, and the tags, going by instinct, almost like perfect pitch applied to speech. Meanwhile, in chat, we traded messages half in Hungarian and half in Italian: a “nevet” thrown in here and there (it means “laughs”, Google taught us that) so we wouldn’t give in to tears instead. In the end, that satisfaction was well earned.

The language industry, caught between crisis and growth

I can’t promise the linguistic quality was flawless. If the transcripts contained errors in meaning, we probably missed some of them, even though Grammarly bailed us out more than once. On the technical side, though, the files met every single requirement set by a client ranking among the world’s top ten tech companies, with each segment and each tag exactly where it belonged.

The paradox is that all this is happening while the industry goes through a period of real uncertainty. The global language services market is worth roughly 76 billion dollars in 2025 and is expected to top 147 billion by 2034, growing at an estimated 7.6% a year. The numbers, however, don’t tell the whole story: research from CEPR estimates that the spread of Google Translate has slowed the creation of about 28,000 translator jobs in the United States between 2010 and 2023, and more than three translators in four expect generative AI to hurt their future earnings. A survey by Acolad among industry professionals backs up that picture: over half say they’re seriously worried about the profession’s future, while 84% expect demand for pure translation to shrink in favor of post-editing. I already touched on this when I wrote about how localization went from fax machines to AI in barely one generation, and the pace of change shows no sign of slowing.

Why betting on a talent is never a mistake

With language skills now taken for granted by so many, I’ve more than once questioned the choice I made thirty-five years ago: studying foreign languages through a degree in translation and interpreting, followed by a master’s in languages and literature. The answer, after this Hungarian experience, came on its own. I bet on an aptitude that gives me joy, real results, and the feeling of having solved a genuine puzzle. That can never be a mistake, whatever the job market says.

Sure, I don’t earn as much as the engineers everyone wants right now, and the AI-driven reshaping of the labor market spares no field, mine included. But I’ve always found a way to reinvent myself: through every reorg, every layoff, every shift in the industry landscape. I’ll keep doing it for as long as I have the persistence to keep learning. Then again, if tech companies are now also hunting for humanities graduates alongside engineers, there must be a reason. And if language talent, like the one on the Hungarian team, is still in demand despite everything, maybe my bet from thirty-five years ago wasn’t so reckless after all.