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You might have noticed that I’m on a bit of hiatus this month. I’m working on my dissertation and preparing applications for post-grad-school jobs, but luckily something I’d done a little while ago has come through the pipeline for me to share.

Back in June, I presented a portion of my dissertation research at the NAACL-HLT conference, but all I had at the time was a computationally-dense paper to show you.  Well, the conference has uploaded videos of all the presentations, so if you’re interested in what I actually do academically, you can find out.  In short, this portion of my research is about the improvements in word segmentation that happen when you combine multiple types of information instead of using a single type.  It’s a computational model of how infants could use additional information to learn words better, as well as learning the likely stress patterns for words in the language they’re learning.

The video [20 min, plus questions that are unfortunately hard to hear]

I tried to make the talk approachable to the non-specialist, so take a gander if you want to see some of my dissertation research (which, of course, is pretty far afield from the discussions on this blog).  There will be math, too, in case you are a specialist, and if you want the whole story, you can see the paper that accompanies the talk.

In other news, I’ll be giving a talk on some of my new research showing how Twitter can be used to map the range of dialectal syntactic variants (e.g., double modals like might could and the needs done construction) at the LSA annual meeting in Minneapolis on January 3.  Check out the abstract here, and maybe I’ll see you there!

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About The Blog

A lot of people make claims about what "good English" is. Much of what they say is flim-flam, and this blog aims to set the record straight. Its goal is to explain the motivations behind the real grammar of English and to debunk ill-founded claims about what is grammatical and what isn't. Somehow, this was enough to garner a favorable mention in the Wall Street Journal.

About Me

I'm Gabe Doyle, currently a postdoctoral scholar in the Language and Cognition Lab at Stanford University. Before that, I got a doctorate in linguistics from UC San Diego and a bachelor's in math from Princeton.

In my research, I look at how humans manage one of their greatest learning achievements: the acquisition of language. I build computational models of how people can learn language with cognitively-general processes and as few presuppositions as possible. Currently, I'm working on models for acquiring phonology and other constraint-based aspects of cognition.

I also examine how we can use large electronic resources, such as Twitter, to learn about how we speak to each other. Some of my recent work uses Twitter to map dialect regions in the United States.



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