corpus-based research

Some thoughts on Healey et al (2014) failure to find syntactic priming in conversational speech

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In a recent PLoS one article, Healey, Purver, and Howes (2014) investigate syntactic priming in conversational speech, both within speakers and across speakers. Healey and colleagues follow Reitter et al (2006) in taking a broad-coverage approach to the corpus-based study of priming. Rather than to focus on one or a few specific structures, Healey and colleagues assess lexical and structural similarity within and across speakers. The paper concludes with the interesting claim that there is no evidence for syntactic priming within speaker and that alignment across speakers is actually less than expected by chance once lexical overlap is controlled for. Given more than 30 years of research on syntactic priming, this is a rather interesting claim. As some folks have Twitter-bugged me (much appreciated!), I wanted to summarize some quick thoughts here. Apologies in advance for the somewhat HLP-lab centric view. If you know of additional studies that seem relevant, please join the discussion and post. Of course, Healey and colleagues are more than welcome to respond and correct me, too.

First, the claim by Healey and colleagues that “previous work has not tested for general syntactic repetition effects in ordinary conversation independently of lexical repetition” (Healey et al 2014, abstract) isn’t quite accurate.

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And a belated welcome to Scott Grimm

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Scott Grimm just joined our faculty in Linguistics at Rochester last month. So today he got his belated Rochester welcome:

South Wedge represents
The South Wedge sends a warm welcome to Scott Grimm

Scott joins the Center of Language Sciences at Rochester with an unnecessary number of degrees. Read the rest of this entry »

Is my analysis problematic? A simulation-based example

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This post is in reply to a recent question on in ling-R-lang by Meredith Tamminga. Meredith was wondering whether an analysis she had in mind for her project was circular, causing the pattern of results predicted by the hypothesis that she was interested in testing. I felt her question (described below in more detail) was an interesting example that might best be answered with some simulations. Reasoning through an analysis can, of course, help a lot in understanding (or better, as in Meredith’s case, anticipating) problems with the interpretation of the results. Not all too infrequently, however, I find that intuition fails or isn’t sufficiently conclusive. In those cases, simulations can be a powerful tool in understanding your analysis. So, I decided to give it a go and use this as an example of how one might approach this type of question.

Results of 16 simulated priming experiments with a robust priming effect (see title for the true relative frequency of each variant in the population).
Figure 1: Results of 16 simulated priming experiments with a robust priming effect (see title for the true relative frequency of each variant in the population). For explanation see text below.

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Correlation plot matrices using the ellipse library

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My new favorite library is the ellipse library. It includes functions for creating ellipses from various objects. It has a function, plotcorr() to create a correlation matrix where each correlation is represented with an ellipse approximating the shape of a bivariate normal distribution with the same correlation. While the function itself works well, I wanted a bit more redundancy in my plots and modified the code. I kept (most of) the main features provided by the function and I’ve included a few: the ability to plot ellipses and correlation values on the same plot, the ability to manipulate what is placed along the diagonal and the rounding behavior of the numbers plotted. Here is an example with some color manipulations. The colors represent the strength and direction of the correlation, -1 to 0 to 1, with University of Rochester approved red to white to blue.

First the function code:

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Compiling TGrep2 on an Intel Macintosh

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When TGrep2 (Ed: a search tool for syntactic corpora in Penn Treebank format) was originally written, all Macs were PPC, but since late 2006 all Macs have been x86 and newer ones are even x86_64. In order to compile tgrep2 on an Intel Mac you have to make some small modifications to the TGrep2 and DRUtils source directories before you compile. This fix at least works on MacOS X 10.5 and 10.6. (Apologies for WordPress mangling the <code> blocks.)

First the patch for DRUtils:
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New Paper on Phonetic Variation over Time

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Max Bane (UChicago, LING), Morgan Sonderegger (UChicago, CS) and I just finished a proceedings paper about our work on phonetic variation. We tracked the VOT distributions of 4 contestants in the reality TV show Big Brother (Season 9, UK) over 3 months and obtained preliminary results showing that social perturbations can potentially explain non-linearities in phonetic parameters over time. Below is a link to our paper. We would be extremely grateful for feedback.

Bane, Max, Peter Graff and Morgan Sonderegger. 2010. Longitudinal Phonetic Variation in a Closed System.

If you would like to hear more about our project, come hear us talk at the LSA in Pittsburgh:

Session 21: Social Factors in Variation
Room: Benedum
Time: Friday, January 7th, 2011 at 9AM

Watch the OCP rock Google’s ngram viewer

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Thanks to Zach Warren for pointing me to this cool tool by Google: the ngram viewer.

And just as a demonstration of how cool this is: watch how the OCP rocks that-mention in complement clauses to the verb believe. Of course, we would have to check for other complement clause embedding verbs and for the a priori probability of this vs. that determiner and pronoun uses. And no, that will be my paper. So don’t you dare write it. If you into OCP effects on optional function word use (e.g. because they might be taken to argue for phonological effects on grammatical encoding), see the references below.

And here are some more verbs for those complement clause lovers out there:
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