I translated "How to use Web?" into some other language using machine translation, but after I translated the result back into English, it is not the same as the first text I put into the translator.
Why did that happen?
I translated "How to use Web?" into some other language using machine translation, but after I translated the result back into English, it is not the same as the first text I put into the translator.
Why did that happen?
There is no one-to-one correspondence between languages and their vocabularies. This means it is impossible for a computer translator to be invertible. The translator's task going from language A to B is fundamentally different from going from language B to A.
To understand this, consider the French word "allumette", which in English is "match", that is, the short piece of wood that can be used to start a fire. A computer translator could easily translate "allumette" into the English word "match". There really is no other way to translate it (though I may be unaware of some idiomatic uses that should be translated another way). But it's not so easy in the other direction.
That's because the English word "match" has many meanings - it also can mean a soccer match ("le match" in French) or it can be a verb, which may be translated as "associer", "assortir", or other verbs. So whereas the translation from French "allumette" to English gave only one choice to the translator - "match", the translation of English "match" to French gives the translators many choices. And they may not get it right.
For example, "I lit the match" translates into French "J'ai allumé le match". Here, the incorrect word "match" (e.g. soccer match) was chosen instead of "allumette".
Even if the translator were perfect, it couldn't even deal with this perfectly - in the sentence "I saw the match", does match refer to a sports contest or something to start a fire? Both could be correct, and without context even a good human translator could only guess.
There is no one-to-one correspondence between languages and their vocabularies. It is fundamentally different from translating A to B and translating B to A in any machine translation software.
For example, when I translate "What is the nearby station?" into Chinese with Google Translate, Google Translate translates this sentence to "什么是附近的车站?" and when I translate back, Google Translate translates "什么是附近的车站?" to "What is a nearby station?" instead of "What is the nearby station?".
That's because the word "是" has many different meanings in Chinese. It could mean "a (一个 in Chinese)" or "the (该 in Chinese)", so both meanings are ok.
The wrong word when I translate back to English is "a". The correct word should be "the" and that's because the word "是" has many different meanings in Chinese, based on the second sentence of this answer.
The correct translation should be "什么是该附近的车站?", and this would translate to "What is the nearby station?". Google Translate translates "What is the nearby station?" to "什么是附近的车站?" instead of "什么是该附近的车站?". It didn't clarify the word "是" by adding "该" to the front of "是". You need to clarify the word "是" and this is because this word in Chinese has many different meanings, based on my second sentence.
By adding "该" to the front of "是", this would clarify the sentence "什么是附近的车站?", because the word "是" has many different meanings in Chinese, based on my fourth sentence at the end and my second sentence. Google Translate doesn't add "该" to the front of "是", and this is why it is not the same as the first time you translate it. If Google Translate adds "该" to the front of "是", it would be same as the first time you translate it.
If we just restrict considering to the vocabulary, the cause of the discrepancy between the source and the source translated to a target then bak to the source is from two three things:
From the first problem, it's easy to see that on the translation from source to target, there are many possibilities, but then from those many possibilities back to the source language, there are that many more possibilities increasing the likelihood of missing the original. The second problem prevent limiting the possibilities to one in each translation.
If we include now add syntax to the context, it may reduce the possibilities, but in some sense a syntactic pattern (like an implication or tense/aspect) in one language doesn't always translate exactly to that in another, so it is almost like a polysemic vacabulry item itself.