Friday, May 6, 2011

Thoughts on Heinz (2010a + b)

Again, I was surprised by how fast I read through these two papers - Heinz definitely knows how to explain abstract concepts in very comprehensible ways. One thing I did notice about these papers was that there were parts that whirled by almost a little too quickly, so that instead of giving background for someone not already in the know about computational phonology, they felt more like a brief literature review for someone already familiar with the relevant concepts. Still, I liked that Heinz was pretty up front about the goal of computational phonology - identifying the shape of the human phonological system (its universal properties, etc.). This definitely feels like a cognitive science-oriented approach, even if the specifics sometimes seem a little disconnected from what we might normally think of as the psychology of language.

Some more specific thoughts:

  • The discussion of finding a theory with the right balance between restrictiveness and expressiveness reminded me very much of Bayesian inference (find the hypothesis that has the best balance between simplicity and fit).

  • My inner theoretical computer science geek was pretty happy about the discussion of problems and algorithms and tractability, and the like. When discussing determinism, though, I do think there's some wiggle room with respect to non-deterministic processes (i.e., those that guess when unsure). A number of acquisition models incorporate some aspect of probabilistically-informed guessing, with reasonable success.

  • I thought the outline of phonological problems in particular (on p.9 of the first paper) neatly described a number of different interesting questions. I think the recognition problem is something like what psycholinguists would call parsing, while the phonotactic learning problem is what psycholinguists would generally call acquisition.

  • I believe Heinz mentions that transducers aren't necessarily the mental representation of grammars, but a lot of the conclusions he mentions seems predicated on that being true in order for the conclusions to have psychological relevance. That is, if the mental representations of grammar aren't something like the transducers discussed here, how informative is it to know that a surface form can be computed in so many steps, etc.? Or maybe there's still a way to translate that kind of conclusion, even if transducers aren't similar to the grammar representation?

  • The fact that two grammar formalisms (SPE and 2LP) are functionally the same is an interesting conclusion. What should then choose between them, besides personal preference? Ease of acquisition maybe?

  • I really liked the discussion distinguishing simulations from demonstrations. I think that pretty much all of my recent models seem to fall more under the demonstration category.

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