adaptation
Two post-doc positions available in our lab
- Project 1: Inference and learning during speech perception and adaptation
- Project 2: Web-based self-administered speech therapy
Although we mention preferred specializations below, applicants from any fields in the cognitive and language sciences are welcome. While candidates will join an active project, candidates are welcome/encouraged to also develop their own independent research program. In case of doubt, please contact Florian Jaeger at fjaeger@bcs.rochester.edu, rather than to self-select not to apply.
Speech perception and generalization across talkers
We recently submitted a research review on “Speech perception and generalization across talkers and accents“, which provides an overview of the critical concepts and debates in this domain of research. This manuscript is still under review, but we wanted to share the current version. Of couse, feedback is always welcome.
In this paper, we review the mixture of processes that enable robust understanding of speech across talkers despite the lack of invariance. These processes include (i) automatic pre-speech adjustments of the distribution of energy over acoustic frequencies (normalization); (ii) sensitivity to category-relevant acoustic cues that are invariant across talkers (acoustic invariance); (iii) sensitivity to articulatory/gestural cues, which can be perceived directly (audio-visual integration) or recovered from the acoustic signal (articulatory recovery); (iv) implicit statistical learning of talker-specific properties (adaptation, perceptual recalibration); and (v) the use of past experiences (e.g., specific exemplars) and structured knowledge about pronunciation variation (e.g., patterns of variation that exist across talkers with the same accent) to guide speech perception (exemplar-based recognition, generalization).
CUNY 2015 plenary
As requested by some, here are the slides from my 2015 CUNY Sentence Processing Conference plenary last week:
I’m posting them here for discussion purposes only. During the Q&A several interesting points were raised. For example Read the rest of this entry »
HLP Lab at CUNY 2015
We hope to see y’all at CUNY in a few weeks. In the interest of hopefully luring to some of our posters, here’s an overview of the work we’ll be presenting. In particular, we invite our reviewers, who so boldly claimed (but did not provide references for the) triviality of our work ;), to visit our posters and help us mere mortals understand.
- Articulation and hyper-articulation
- Unsupervised and supervised learning during speech perception
- Syntactic priming and implicit learning during sentence comprehension
- Uncovering the biases underlying language production through artificial language learning
Interested in more details? Read on. And, as always, I welcome feedback. (to prevent spam, first time posters are moderated; after that your posts will always directly show)
Presentation at CNS symposium on “Prediction, adaptation and plasticity of language processing in the adult brain”
Earlier this week, Dave Kleinschmidt and I gave a presentation as part of a mini-symposium at Cognitive Neuroscience Conference on “Prediction, adaptation and plasticity of language processing in the adult brain” organized by Gina Kuperberg. For this symposium we were tasked to address the following questions:
- What is prediction and why do we predict?
- What is adaptation and why do we adapt?
- How do prediction and adaptation relate?
Although we address these questions in the context of language processing, most of our points are pretty general. We aim to provide intuitions about the notions of distribution, prediction, distributional/statistical learning and adaptation. We walked through examples of belief-updating, intentionally keeping our presentation math-free. Perhaps some of the slides are of interest to some of you, so I attached them below. A more in-depth treatment of these questions is also provided in Kleinschmidt & Jaeger (under review, available on request).
Comments welcome. (sorry – some of the slides look strange after importing them and all the animations got lost but I think they are all readable).
It was great to see these notions discussed and related to ERP, MEG, and fMRI research in the three other presentations of the symposium by Matt Davis, Kara Federmeier and Eddy Wlotko, and Gina Kuperberg. You can read their abstracts following the link to the symposium I included above.
Post-doctoral position available (speech perception, language comprehension, implicit distributional learning, inference under uncertainty, hierarchical predictive systems)
The Human Language Processing (HLP) Lab at the University of Rochester is looking for a post-doctoral researcher interested in speech perception and adaptation. Possible start dates for this 1-3 year position range from mid August 2014 to mid June 2015 (the current post-doctoral researcher funded under this grant will leave HLP lab in late August to start a tenure-track position in Psychology at the University of Pittsburgh). International students are welcome to apply (NIH research grants are not limited to nationals).
We will start reviewing applications mid-June 2014 though later submissions are welcome. Applications should contain (1) a cover letter clearly indicated possible start dates, (2) a CV, (3) research statement detailing qualifications and research interests, and (4) 2 or more letters of recommendation. Applications and letters should be emailed to Kathy Corser (kcorser@bcs.rochester.edu), subject line “application for post-doc position (HLP Lab)”.
This is an NIH funded project (NIHCD R01 HD075797), currently scheduled to end in 2018. The project is a collaboration between Florian Jaeger (PI), Mike Tanenhaus (co-PI), Robbie Jacobs and Dick Aslin. We are interested in Read the rest of this entry »
Socially-mediated syntactic alignment
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 »
Perspective paper on second (and third and …) language learning as hierarchical inference
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 »
A few reflections on “Gradience in Grammar”
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 »
“Gradience in Grammar” workshop at CSLI, Stanford (#gradience2014)
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
HLP Lab is looking for graduate researchers
The Human Language Processing (HLP/Jaeger) Lab in the Department of Brain and Cognitive Sciences at the University of Rochester is looking for PhD researchers to join the lab. Admission is through the PhD program in the Brain and Cognitive Sciences, which offers full five-year scholarship. International applications are welcome.
Syntactic expectation adaptation (update your beliefs!)
At long last, Alex Fine‘s paper on syntactic adaptation expectation is about to appear in PLOS One. You can download the pre-proof from our academia.edu page (the final version will be linked there as soon as it’s available):
- Fine, A. B., Jaeger, T. F., Farmer, T. , and Qian, T. 2013. Rapid expectation adaptation during syntactic comprehension. PLoS One.
The paper presents a novel framework that ties together syntactic comprehension and implicit learning. We tie together work on expectation-based sentence understanding, syntactic priming in comprehension, statistical learning, and speaker-specificity in syntactic comprehension.
In two self-paced reading studies, we show that readers rapidly adjust their expectations for specific syntactic structures to converge on the statistics of the current environment. They do so based on both previous experience and recent experience within the experiment. Read the rest of this entry »
congratulations to Ting Qian and Dave Kleinschmidt
Congratulations to Ting Qian and Dave Kleinschmidt, both students in the Brain and Cognitive Science Program at Rochester and members of HLP Lab, for being awarded a Google Travel Grant to CogSci 2012 in Sapporo, Japan, where they will present their work. which centers around implicit statistical learning and adaptation during language acquisition and processing:
- Qian, T., Reeder, P.A., Aslin, R.N., Tenenbaum, J.B., and Newport, E.L. 2012. Exploring the Role of Representation in Models of Grammatical Category Acquisition. In TBA (eds.) Proceedings of the 34th Annual Meeting of the Cognitive Science Society (CogSci12), TBA. Austin, TX: Cognitive Science Society.
- Kleinschmidt, D. and Jaeger, T. F. 2012. A continuum of phonetic adaptation: Evaluating an incremental belief-updating model of recalibration and selective adaptation. In TBA (eds.) Proceedings of the 34th Annual Meeting of the Cognitive Science Society (CogSci12), TBA. Austin, TX: Cognitive Science Society.
- Kleinschmidt, D., Fine, A. B., and Jaeger, T. F. 2012. A belief-updating model of adaptation and cue combination in syntactic comprehension. In TBA (eds.) Proceedings of the 34th Annual Meeting of the Cognitive Science Society (CogSci12), TBA. Austin, TX: Cognitive Science Society.
And, thank you, dear Google.
CogSci 2011 papers uploaded
In case, there’s interest, have a look at the papers to be presented at this year’s Cognitive Science meeting in Boston (July, 20th-23rd). HLP lab will be represented by two talks and four posters. The two talks will presenting work employing artificial language learning to address questions about typological generalizations:
- Masha Fedzechkina(BCS, University of Rochester) will present evidence that language learners are biased to reduced the uncertainty in the mapping from form to meaning. Her work is comparing the acquisition of miniature languages with and without case-marking in terms of to what extent learners tend to regularize or even fix variable word orders for these two types of languages (Fedzechkina, Jaeger, & Newport, 2011). Together with other recent work (e.g. by Newport, by Culbertson), this work provides evidence that language learners deviate from the input provided to them in a predictable manner. In this case, we designed the experiment to directly test the functionalist claim that language learners are biases towards acquiring languages that support communication (cf. Bates and MacWhinney’s early work).
- Hal Tily (BCS, MIT) will present work employing a novel web-based artificial language learning paradigm, in which hundreds of participants can be run within a matter of a few days. Using this paradigm, we first replicated and extended a well-known study on determiner learning (Hudson Kam and Newport, 2004) and then investigate to what extent cross-linguistically observed quantitative patterns in argument and determiner order are replicated by language learners. We discuss how this paradigm will facilitate further tests of typological generalizations (Tily, Frank, & Jaeger, 2011).
HLP/Jaeger lab blog 