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

18 April, 2022

25 April, 2022

Deadline extended! Due to Easter, we have extended the deadline by one week.

(Midnight, GMT -12. That is, submission will stay open as long as it's still 25 April anywhere in the world.)

Notification of acceptance

17 June, 2022

Revised abstracts due

1 July, 2022

Conference

1-3 August, 2022

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
  • learning models such as Hebbian learning, statistical learning, Bayesian learning or distributional learning, especially if a connection can be made to error-driven learning.
CALL FOR ABSTRACTS IS NOW CLOSED

Presentation guidelines

Please see the Platform page for more details about the talk and poster sessions in the gather town space.

Talks

The talks will be held in gather.town lecture hall. Each talk slot is 18+7 = 25 minutes. Presentation time is 18 minutes. After the presentation, 7 minutes are reserved for questions, discussion, 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 by July 27, 2022 as a PDF file.

Invited Speakers

Peter Dayan

(Max Planck Institute for Biological Cybernetics)

Generative and discriminative reinforcement learning as model-based and model-free control

Elizabeth Wonnacott

(University of Oxford)

Language input and generalization:
Evidence from language learning experiments with adults and children

Padraic Monaghan

(University of Lancaster and University of Amsterdam)

How multiple and multimodal sources of information support word learning

Jacolien van Rij

(University of Groningen)

Contact

For inquiries please contact: