machine translation bias removal tool
Machine translation in Czech

Finally, a translation app that knows the difference between Czech ‘ty’ and ‘vy’!

Wouldn’t it be nice if machine translation asked how you want to translate ‘you’?

Let’s do a little experiment: go to your favourite machine translation website, such as Google Translate, and ask it to translate a sentence from English into Czech which has the pronoun you in it. Will it be translated as the informal casual ty, or as the formal polite vy? It’s anyone’s guess really, most machine translators seem to choose one or the other pretty much arbitrarily.

In case you didn’t know, Czech is one of those languages where you have two ways or “levels” of talking to people. People you are close to, such as friends and family, you address them with the informal pronoun ty. People you are more distant with, strangers you’ve just met and so on, you address them with the formal pronoun vy. English has only one word for both levels, the pronoun you, so this distinction doesn’t really exist in English. But in most European languages it does, including Czech.

Back to machine translation. Wouldn’t it be nice if your machine translator simply asked you which level of formality you wanted, instead of guessing? Because guessing is what the machines do, mostly. Machines are good at computing likelihoods and probabilities, so they are able to guess which level of formality is more “normal” or “usual” for any sentence, based on the data they have been trained on. The only problem is, this might be the complete opposite of what you have in mind at this very moment. Suppose you’re translating something ordinary, such as please sit down or are you hungry? How is a machine supposed to guess correctly who you’re saying it to? To your grandson? To your mother-in-law? Or to a customer in your restaurant? Which level of formality is required? No artificial intelligence can ever guess what only you can know. (By the way, it’s ty for the grandson and vy for the customer, the mother-in-law is a borderline case.)

Fairslator is a machine translator that doesn’t try to guess such things. Fairslator asks you instead. In Fairslator, if you tell it to translate something with you in it, you will be offered a list of options where you can select what exactly you mean by that you: which level of formality, and also whether it’s supposed to be a singular you (when you’re talking to one person) or a plural you (when you’re talking to several people).

Can your usual machine translator do that? Probably not. As far as we know, Fairslator is the first and only translation service in the world that doesn’t just spit out one single translation, but asks you what you mean by that. Try it for yourself and tell all your Czech-speaking friends – but don’t forget to use the correct version of you!

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Faislator blog

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Tusa, sibhse agus an meaisínaistriúchán ó Bhéarla
Tugaimis droim láimhe leis an mhíthuiscint nach bhfuil ach aon aistriúchán amháin ar gach rud.
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Stell dir vor, du bist DeepL
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Fairslator timeline

icon September 2022 — Fairslator was presented and demoed at the Text, Speech and Dialogue (TSD) conference in Brno.
icon August 2022Translations in London are talking about Fairslator in their blog post Overcoming gender bias in MT. They think the technology behind Fairslator could be useful in the translation industry for faster post-editing of machine-translated texts.
August 2022 — A fourth language pair released: English → French.
icon July 2022 — Germany's Goethe-Institut interviewed us for the website of their project Artificially Correct. Read the interview in German: Wenn die Maschine den Menschen fragt or in English: When the machine asks the human, or see this short video on Twitter.
icon May, a website for the translation industry, asked us for a guest post and of course we didn't say no. Read What You Need to Know About Bias in Machine Translation »
April 2022 — A third language pair added: English → Irish.
February 2022 — Fairslator launched with two language pairs: English → German, English → Czech. Cries of excitement from everywhere!