It's the consequence of translation engines being trained on a corpus that is mainly Spanish and English. Meaning, that most txt in other languages have been translated to either Spanish or english, and those translations are what is used to train contextual inference for translations. It needs a corpus of text of two languages to even attempt translation from A to B. If it doesn't have enough, it will use bridge languages.
How many texts are there both in Ukrainian and Japanese? Effectively none, so it makes perfect sense to use a bridge language. The issue here is that the context wasn't properly kept in the bridging, and they should theoretically be able to do that. A buddy I shared my master's with was Iranian and he explained the semantic context issue to me, he was working on exactly this issue.
The middle language is not a spoken language. Googles AI created an intermediary language (like 10+ years ago) to translate between all languages. It's not written/spoken, it's done on weights. It's referred to as an 'interlingua'
You notice it when you look at international instructions on packets of food. The non-English texts have a distinct English vibe even when the product is, say, French or German.
The way translation engines are trained is with a body of written text in two languages, which teaches the engine both how words translate and how they fit in equivalent semantic contexts. That way it can decide which synonym is the best one to use given the context, and lose the least amount of context in the bridging.
Of course a person as put in effort, so has in every language. But that's irrelevant if there isn't a large body of text in both languages to learn from. I'm sure German and Dutch have a looooot of shared texts.
Yeah, in my experience it absolutely does translate everything via English. If you need to translate from Ukranian directly to other languages, ironically Yandex Translate is probably your best bet. It's worse at Russian <-> English and Ukranian <-> English but much better at direct pairs between other languages.
Are they? I know that its been that way years ago, but now with ai technology, it should be able to translate text not just by the word definition, but also context and conceptual meaning. At lest it is supposed to work this way if they used ai for actually useful stuff and not another slop generator.
it should be able to translate text not just by the word definition, but also context and conceptual meaning.
It has been doing that at least since 2016, and it's using LLM-adjacent tech (transformer + RNN) since 2020. The problem is that it still seems to be doing things via English, which is especially problematic for single words with no context. In this example, "зачиняти" means "to close". Google translates it to English as simply "close", which loses the context of which meaning or even part of speech it is. Google then translates it to Japanese, but since the context is lost it assumes that "close" means "near" rather than "block an opening" and translates it as "chikai".
(actually, Yandex Translate fucks this up as well and translates "зачиняти" as "黙れ" (shut up), which is somehow worse)
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