7 ms·

Are you sure that this particular translation is "nonsense"? To me, it seems almost perfect. The only mistake in the French version is the gender of the teacher

Are you sure that this particular translation is "nonsense"? To me, it seems almost perfect. The only mistake in the French version is the gender of the teacher, which is a mistake that many humans can and do make, in addition to many other mistakes...

puszczyk 9y ago
Well, the Greek version says she-teacher and it translates to French he-teacher. Def a big mistake. Note this is not the same as messing up if eg some random butterfly you see is he or she in French. The context is there, but google translate seems to convert everything to English, loosing some meaning in the process. It don’t want to say google translate is a complete garbage. On the contrary, I use it often e.g to plan my holiday trips or shop online in other EU countries. Nevertheless, I rarely translate anything to my native language, but rather to English. It the auto translation made a great progress and it is very useful, but it has a long way to go still.
- 1024core 9y ago
  > Well, the Greek version says she-teacher and it translates to French he-teacher. Def a big mistake. I have Mandarin speaking friends (graduates of US universities), for whom English is a second language. They often use "she" instead of "he" (or vice versa) when referring to others. If humans, who have been using English for 7-8 years, can't get this right, then I wouldn't call it a "big mistake". It is a mistake, for sure; but it's not the end of the world.
  - YeGoblynQueenne 9y ago
    Your friends however will be able to keep track of the references to the same person in a conversation, even if they get the gender wrong. In GT's case it's evidence that it can't do that, and therefore will mangle longer passages that require this level of understanding.
    - 1024core 9y ago
      Actually, no. Just a couple of days ago, when talking about a female colleague, they kept switching from "he" to "she" and back and forth. It's almost as if Mandarin has no "he" or "she" equivalents.
      - YeGoblynQueenne 9y ago
        But they were still talking about the same person, yes? That's what I mean about the references being constant. For humans, anaphora resolution is child's play. For computers, it's very tricky.
deleted 9y ago
[deleted]
YeGoblynQueenne 9y ago
In a way, it's literally nonsense, in the, uh, sense that it can't makey any sense of what it's translating and is just choosing some output string at random (i.e. with probability drawn from some distribution it has derived from its training examples). Of course that's not what I mean above. Yes, the string I present is an example of the nonsense that comes out of purely statistical machine translation. It's a simple example and a very simple sentence, but that sort of noun-pronoun disagreement can completely distort the meaning of more complex sentences, not to mention longer passages where there are references to multiple persons across sentence boundaries. Here's another example (original text by myself): Πήγαμε με τη Βασιλική να δούμε το Μήτσο στο νοσοκομείο. Είχε σπάσει το πόδι του και του βάλανε λάμες. Η Βασιλική, που είναι λίγο καψούρα μαζί του, του πήρε κάτι σοκολάτες και λουλούδια, σα χαζό κοριτσάκι από καμμιά ρομαντική σειρά. Εγώ πήγα για συμπαράσταση λαέ. Το χειρότερο ξέρεις ποιό είναι; Όχι μόνο ήτανε εκεί η μάνα του, ο πατέρας του κι η αδερφή του, αλλά ήτανε κι η Μαρία, που τά 'χανε πέρσι. Καταστροφή! Google translates: We went with Vassiliki to see Mitsos in the hospital. He had broken his leg and he put blades on him. Basilica, who is a little bit of mascara with him, got something chocolates and flowers, like a stupid little girl from any romantic series. I went for support. Worst you know who it is? Not only was the mother there his father and his sister, but she was Maria, who lost her last year. Destruction! My intended meaning: Me and Vassiliki went to see Mitsos at the hospital. He had broken his leg and he had to have metal plates inserted. Vassiliki, who has a bit of a crush on him, got him some chocolates and flowers, like a silly little girl from some rom-com. I just went along for solidarity. And you know what the worse part is? His mother and father and his sister were there and not just them, but also Maria his ex from last year. Disaster! Examples like this reinforce my intuition that, in translation, it's impossible to get correct results while starting from the wrong premises. If you think about maths, for example. I'm pretty sure that you can train a statistical model (a translation model, actually) to try and generate results of various mathematical expressions. It's easy to see that such a model would often get the wrong results, because of a lack of any understanding of mathematics. In fact, you could very accurately say that it would produce a lot of nonsense. And even if it got the right answer- what would that prove? It would still be obvious that it doesn't know how to solve maths problems, just guess at their more likely solution. It's also easy to see that we don't use statistical models to solve maths problems, because we don't need them: we know the rules of arithmetic etc that lead to the correct solutions. With translation, we don't know what those rules are (if they can even be represented as rules) so we go for statistical models instead- but that is only because we can't do anything better. Statistical machine translations are fundamentally flawed. They might be "good enough" for some situations, but they are effectively designed to fail, by not even trying to solve the actual problem of translation. And so what they produce is nonsense- and it is nonsense even when it looks like it sorta, kinda makes sense. It's nonsense because it's basically, just random.
claforte 9y ago
I'm a french native (from Quebec) and to me, there is no mistake. We'd often say "Ma professeure" for the feminine. Maybe in France or other countries they are more formal. Either way, this isn't a good example of Google Translate limitation.

puszczyk 9y ago

Well, the Greek version says she-teacher and it translates to French he-teacher. Def a big mistake. Note this is not the same as messing up if eg some random butterfly you see is he or she in French. The context is there, but google translate seems to convert everything to English, loosing some meaning in the process. It don’t want to say google translate is a complete garbage. On the contrary, I use it often e.g to plan my holiday trips or shop online in other EU countries. Nevertheless, I rarely translate anything to my native language, but rather to English. It the auto translation made a great progress and it is very useful, but it has a long way to go still.

1024core 9y ago
> Well, the Greek version says she-teacher and it translates to French he-teacher. Def a big mistake. I have Mandarin speaking friends (graduates of US universities), for whom English is a second language. They often use "she" instead of "he" (or vice versa) when referring to others. If humans, who have been using English for 7-8 years, can't get this right, then I wouldn't call it a "big mistake". It is a mistake, for sure; but it's not the end of the world.
- YeGoblynQueenne 9y ago
  Your friends however will be able to keep track of the references to the same person in a conversation, even if they get the gender wrong. In GT's case it's evidence that it can't do that, and therefore will mangle longer passages that require this level of understanding.
  - 1024core 9y ago
    Actually, no. Just a couple of days ago, when talking about a female colleague, they kept switching from "he" to "she" and back and forth. It's almost as if Mandarin has no "he" or "she" equivalents.
    - YeGoblynQueenne 9y ago
      But they were still talking about the same person, yes? That's what I mean about the references being constant. For humans, anaphora resolution is child's play. For computers, it's very tricky.

deleted 9y ago

[deleted]

YeGoblynQueenne 9y ago

In a way, it's literally nonsense, in the, uh, sense that it can't makey any sense of what it's translating and is just choosing some output string at random (i.e. with probability drawn from some distribution it has derived from its training examples). Of course that's not what I mean above. Yes, the string I present is an example of the nonsense that comes out of purely statistical machine translation. It's a simple example and a very simple sentence, but that sort of noun-pronoun disagreement can completely distort the meaning of more complex sentences, not to mention longer passages where there are references to multiple persons across sentence boundaries. Here's another example (original text by myself): Πήγαμε με τη Βασιλική να δούμε το Μήτσο στο νοσοκομείο. Είχε σπάσει το πόδι του και του βάλανε λάμες. Η Βασιλική, που είναι λίγο καψούρα μαζί του, του πήρε κάτι σοκολάτες και λουλούδια, σα χαζό κοριτσάκι από καμμιά ρομαντική σειρά. Εγώ πήγα για συμπαράσταση λαέ. Το χειρότερο ξέρεις ποιό είναι; Όχι μόνο ήτανε εκεί η μάνα του, ο πατέρας του κι η αδερφή του, αλλά ήτανε κι η Μαρία, που τά 'χανε πέρσι. Καταστροφή! Google translates: We went with Vassiliki to see Mitsos in the hospital. He had broken his leg and he put blades on him. Basilica, who is a little bit of mascara with him, got something chocolates and flowers, like a stupid little girl from any romantic series. I went for support. Worst you know who it is? Not only was the mother there his father and his sister, but she was Maria, who lost her last year. Destruction! My intended meaning: Me and Vassiliki went to see Mitsos at the hospital. He had broken his leg and he had to have metal plates inserted. Vassiliki, who has a bit of a crush on him, got him some chocolates and flowers, like a silly little girl from some rom-com. I just went along for solidarity. And you know what the worse part is? His mother and father and his sister were there and not just them, but also Maria his ex from last year. Disaster! Examples like this reinforce my intuition that, in translation, it's impossible to get correct results while starting from the wrong premises. If you think about maths, for example. I'm pretty sure that you can train a statistical model (a translation model, actually) to try and generate results of various mathematical expressions. It's easy to see that such a model would often get the wrong results, because of a lack of any understanding of mathematics. In fact, you could very accurately say that it would produce a lot of nonsense. And even if it got the right answer- what would that prove? It would still be obvious that it doesn't know how to solve maths problems, just guess at their more likely solution. It's also easy to see that we don't use statistical models to solve maths problems, because we don't need them: we know the rules of arithmetic etc that lead to the correct solutions. With translation, we don't know what those rules are (if they can even be represented as rules) so we go for statistical models instead- but that is only because we can't do anything better. Statistical machine translations are fundamentally flawed. They might be "good enough" for some situations, but they are effectively designed to fail, by not even trying to solve the actual problem of translation. And so what they produce is nonsense- and it is nonsense even when it looks like it sorta, kinda makes sense. It's nonsense because it's basically, just random.

claforte 9y ago

I'm a french native (from Quebec) and to me, there is no mistake. We'd often say "Ma professeure" for the feminine. Maybe in France or other countries they are more formal. Either way, this isn't a good example of Google Translate limitation.