EDLL 2021

Error-driven learning models, such as Rescorla and Wagner (1972) and Widrow and Hoff (1960) have had a major influence on many areas of psychology related to human and animal learning. However, research on language learning took a separate path for a long time. Recently, insights from error-driven learning have begun to be applied to a broad range of language phenomena with very promising results. For example, error-driven learning models have addressed questions relating to reading, spoken word comprehension, colour and number acquisition, word learning, first and second language speech sound acquisition, morphological processing, sentence processing, neural correlates of prediction error and more.

The International Conference on Error-Driven Learning in Language (EDLL 2021) aims to bring together researchers interested in error-driven learning in speech and language.

DATE

March 10-12, 2021

PLATFORM

The conference will be online. See this page for more details.

CONFERENCE CHAIRS

Jessie Nixon
Elnaz Shafaei-Bajestan
Harald Baayen

Also thanks to Adnane Ez-Zizi for help with the programme.

TIMETABLE

Download the timetable here in PDF.

To easily import the timetable to your calendaring software, download the iCal file here in ICS.

Times are given in CET (UTC+1).

This schedule reflects the geographical diversity of our conference delegates from across the globe. We have done our best to accommodate the widely varying time zones.

MATERIALS

Conference proceedings is available here.

REGISTRATION

Registration is closed.

SPECIAL ISSUE on ERROR-DRIVEN LEARNING IN SPEECH AND LANGUAGE

If you’re interested in error-driven learning in language, you may be interested in our upcoming Special Issue to be published in the journal Language, Cognition and Neuroscience: Emergence of speech and language from prediction error: error-driven language models, edited by Jessie Nixon and Fabian Tomaschek. We are due to receive the last submissions in the next few weeks and we anticipate the special issue to be published later in 2021 or early 2022. If you’re interested in being notified when the special issue comes out, please feel free to leave your details here.

This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme under grant agreement No 742545.

Important Dates

Abstracts due

20 December, 2020

(Midnight, GMT -12. That is, submission will stay open as long as it's still 20 December anywhere in the world.)

Notification of acceptance

8 February 2021

Registration deadline

17 February, 2021

Conference

10-12 March, 2021

Call for abstracts: closed

We are inviting experimental, computational or theoretical abstracts on any topic in error-driven learning of speech or language. Suitable topics include but are not limited to:

The role of error in:

first and second language acquisition
learning or processing phonetic, morphological, syntactical or lexical information
sentence processing, syntax and grammar acquisition and processing

as well as

neural processing of error feedback during speech and language comprehension, production or learning
the relationship between error-driven learning and information theory
comparison of error-driven learning with different learning models such as Hebbian learning, statistical learning, Bayesian learning, distributional learning.

CALL FOR ABSTRACTS IS NOW CLOSED

Presentation guidelines

Talks

The presentations will be held in gather.town lecture hall. Presentation time is 20 minutes. After the presentation, 10 minutes are reserved for questions, discussions, and speaker transitions.

Posters

The posters will be presented and discussed in gather.town poster hall. The poster should have the aspect ratio of A0 in portrait mode. Please send the posters to us until March 3, 2021 as a PDF file.

Invited Speakers

Adele E. Goldberg

(Princeton University)

Explain me this:
Coverage encourages generalization and Statistical Preemption constrains it

Randall O'Reilly

(University of California, Davis)

Predictive Error-driven Learning in the Brain

Petar Milin

(University of Birmingham)

What can be used from learning?

Contact

For inquiries please contact:

Jessie Nixon

jessie.nixon@uni-tuebingen.de

Elnaz Shafaei-Bajestan

elnaz.shafaei-bajestan@uni-tuebingen.de