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I think this is the prevailing view within linguistics departments (with a few exceptions). Statistical NLP, machine learning, computational anthropology, devel
by glup 10y ago
I think this is the prevailing view within linguistics departments (with a few exceptions). Statistical NLP, machine learning, computational anthropology, developmental psychology, etc. are all increasingly reliant on the non-generative work coming out of psycholinguistics and child language acquisition (Levy, Jaeger, Gibson, Wasow, Tomasello, Lieven, Bannard if you want some names).
- foldr 10y agoI don't think there's much of a shift there. You're talking about fields which never had much of a connection with generative linguistics, and where there's no logical reason to think that results in generative linguistics should be particularly relevant or helpful. (Who ever thought that Barriers would have anything to tell us about computational anthropology?) Generative linguistics is in fact increasingly relevant to NLP, since people are moving towards more complex language models. That's not to say that cutting edge research in syntax is going to be helpful to people trying to solve practical NLP problems, but by the same token, string theory isn't much use if you're trying to build a bridge. It tends to be the basic and well-established results within a field that have useful applications outside it.