3 ms·

Of note, children demonstrate pretty robust grammatical expectations for specific syntactic phenomena after hearing comparable number of utterances, with confli

by glup 9y ago

Of note, children demonstrate pretty robust grammatical expectations for specific syntactic phenomena after hearing comparable number of utterances, with conflicting evidence regarding the availability or reliability of negative evidence. Of course the proofs you cite from formal work are unassailable (=math), but it's possible that "learning" tolerates more error than identification in the limit (see PAC learning for example), and that developing a facility with natural language has more to do with matching the distributions over strings from the adult grammar than inferring the correct grammar (identifying which utterances are in the language, vs. those that aren't). Child language induction is often used as the model for zero-resource natural language processing. This seems to be the direction Dr. Schuler is coming from: http://aclweb.org/anthology/C/C16/C16-1092.pdf http://aclweb.org/anthology/C/C16/C16-1092.pdf.

YeGoblynQueenne 9y ago
I'm not convinced about the "learning to match the distributions of strings, rather than the full structure of a language" bit. I'm not saying that you can only learn a language in full. For instance, I speak Greek natively and I know a bit of Italian. I don't have to know Italian perfectly to read books (and fumetti) and communicate in it. Then again, I already know a language so the problem of learning a new one is quite a different one from learning the first. The problem I have with statistical language learning, especially in children, is that, just because you can learn a distribution over strings doesn't mean you should, or that you do, as a human. I'll move the goal posts a bit now (but then again, you started talking about language learning in children) but an important ability of language users is that they can produce coherent utterances in context. Statistical language models can learn some structure and parameters, but I have yet to see any statistical learner that can do what humans do, know what it's saying and what is being said. This tells me that, although statistical learning may take us even say half-way to language learning, it won't get us all the way. I'm convinced that there's something much simpler, much easier (in terms of computational operations) that children -and adults- do when they learn language. We just haven't found out what it is, yet. Btw, limited human ability for introspection not withstanding, I can tell that when I try to understand a spoken or written utterance I definitely do something sort of probabilistic- I will sometimes even consciously ask myself what is more likely being said. But that doesn't tell me that language learning, or intelligence itself, is probabilistic- in the same way that just because I can walk I don't think of myself as a pair of legs with stuff on top (accurate as that description might be). Edit: upvote from me, for being the first person on HN that knows what I'm talking about when I'm talking about Gold's result etc. I was starting to think it was all a dream I had.

by glup 9y ago

YeGoblynQueenne 9y ago

I'm not convinced about the "learning to match the distributions of strings, rather than the full structure of a language" bit. I'm not saying that you can only learn a language in full. For instance, I speak Greek natively and I know a bit of Italian. I don't have to know Italian perfectly to read books (and fumetti) and communicate in it. Then again, I already know a language so the problem of learning a new one is quite a different one from learning the first. The problem I have with statistical language learning, especially in children, is that, just because you can learn a distribution over strings doesn't mean you should, or that you do, as a human. I'll move the goal posts a bit now (but then again, you started talking about language learning in children) but an important ability of language users is that they can produce coherent utterances in context. Statistical language models can learn some structure and parameters, but I have yet to see any statistical learner that can do what humans do, know what it's saying and what is being said. This tells me that, although statistical learning may take us even say half-way to language learning, it won't get us all the way. I'm convinced that there's something much simpler, much easier (in terms of computational operations) that children -and adults- do when they learn language. We just haven't found out what it is, yet. Btw, limited human ability for introspection not withstanding, I can tell that when I try to understand a spoken or written utterance I definitely do something sort of probabilistic- I will sometimes even consciously ask myself what is more likely being said. But that doesn't tell me that language learning, or intelligence itself, is probabilistic- in the same way that just because I can walk I don't think of myself as a pair of legs with stuff on top (accurate as that description might be). Edit: upvote from me, for being the first person on HN that knows what I'm talking about when I'm talking about Gold's result etc. I was starting to think it was all a dream I had.