Papers, Presentations, etc.
A few days ago, I posted a summary of some recent work on syntactic alignment with Kodi Weatherholtz and Kathryn Campell-Kibler (both at The Ohio State University), in which we used the WAMI interface to collect speech data for research on language production over Amazon’s Mechanical Turk.
The first step in our OSU-Rochester collaboration on socially-mediated syntactic alignment has been submitted a couple of weeks ago. Kodi Weatherholtz in Linguistics at The Ohio State University took the lead in this project together with Kathryn Campbell-Kibler (same department) and me.
We collected spoken picture descriptions via Amazon’s crowdsourcing platform Mechanical Turk to investigate how social attitude towards an interlocutor and conflict management styles affected syntactic priming. Our paradigm combines Read the rest of this entry »
I’ll be giving a plenary presentation at the 15th Texas Linguistic Society conference to be held in October in Austin, TX. Philippe Schlenker from NYU and David Beaver from Austin will be giving plenaries, too. The special session will be on the “importance of experimental evidence in theories of syntax and semantics, and focus on research that highlights the unique advantages of the experimental environment, as opposed to other sources of data” (from their website). Submit an abstract before May 1st and I see you there.
We’ve just submitted a perspective paper on second (and third and …) language learning as hierarchical inference that I hope might be of interest to some of you (feedback welcome).
- Pajak, B., Fine, A.B., Kleinschmidt, D., and Jaeger, T.F. submitted. Learning additional languages as hierarchical probabilistic inference: insights from L1 processing. submitted for review to Language Learning.
We’re building on Read the rest of this entry »
This workshop on data visualization might be of interest to a lot of you. I wish I could just hop over the pond.
- Date: 24-Sept-2014 – 26-Sept-2014
- Location: Tuebingen, Germany
- Contact Person: Fabian Tomaschek (email@example.com)
- Web Site: http://avml-meeting.com
- Call Deadlines: 21 March / 18 April
The AVML-meeting offers a meeting place for all linguists from all fields who are interested in elaborating and improving their data visualization skills and methods. The meeting consists of a one-day hands-on workshop Read the rest of this entry »
In my earlier post I provided a summary of a workshop on Gradience in Grammar last week at Stanford. The workshop prompted many interesting discussion, but here I want to talk about an (admittedly long ongoing) discussion it didn’t prompt. Several of the presentations at the workshop talked about prediction/expectation and how they are a critical part of language understanding. One implication of these talks is that understanding the nature and structure of our implicit knowledge of linguistic distributions (linguistic statistics) is crucial to advancing linguistics. As I was told later, there were, however, a number of people in the audience who thought that this type of data doesn’t tell us anything about linguistics and, in particular, grammar (unfortunately, this opinion was expressed outside the Q&A session and not towards the people giving the talks, so that it didn’t contribute to the discussion). Read the rest of this entry »
A few days ago, I presented at the Gradience in Grammar workshop organized by Joan Bresnan, Dan Lassiter , and Annie Zaenen at Stanford’s CSLI (1/17-18). The discussion and audience reactions (incl. lack of reaction in some parts of the audience) prompted a few thoughts/questions about Gradience, Grammar, and to what extent the meaning of generative has survived in the modern day generative grammar. I decided to break this up into two posts. This summarizes the workshop – thanks to Annie, Dan, and Joan for putting this together!
The stated goal of the workshop was (quoting from the website):
For most linguists it is now clear that most, if not all, grammaticality judgments are graded. This insight is leading to a renewed interest in implicit knowledge of “soft” grammatical constraints and generalizations from statistical learning and in probabilistic or variable models of grammar, such as probabilistic or exemplar-based grammars. This workshop aims to stimulate discussion of the empirical techniques and linguistic models that gradience in grammar calls for, by bringing internationally known speakers representing various perspectives on the cognitive science of grammar from linguistics, psychology, and computation.
Apologies in advance for butchering the presenters’ points with my highly subjective summary; feel free to comment. Two of the talks demonstrated