LINGUIST List 32.3828

Wed Dec 08 2021

Confs: Cog Sci, Comp Ling, Gen Ling, Lang Acquisition, Psycholing/Germany

Editor for this issue: Everett Green <everettlinguistlist.org>



Date: 02-Dec-2021
From: Jessie Nixon <jessie.nixonuni-tuebingen.de>
Subject: Second International Conference on Error-Driven Learning in Language
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Second International Conference on Error-Driven Learning in Language
Short Title: EDLL 2022


Date: 01-Aug-2022 - 03-Aug-2022
Location: Tübingen/Online, Germany
Contact: Jessie Nixon
Contact Email: < click here to access email >

Linguistic Field(s): Cognitive Science; Computational Linguistics; General Linguistics; Language Acquisition; Psycholinguistics

Meeting Description:

Pre-call Announcement

Dear all,

after the success of the first EDLL (2021) conference earlier this year, we’re pleased to announce that the Second International Conference on Error-Driven Learning in Language (EDLL 2022) will take place next year. This is an informal pre-call announcement, so that you can start thinking about what you would like to present! More details will follow in due course.

We envisage holding the conference in early August 2022, exact date to be confirmed. (Note the later date compared to the 2021 conference). Details regarding abstract submission, deadlines and important dates will follow.

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The Second International Conference on Error-Driven Learning in Language (EDLL 2022) aims to bring together researchers interested in error-driven learning in speech and language.

We would also be interested in submissions from neighbouring fields, such as implicit learning, statistical learning and applied linguistics, especially if a connection can be made to error-driven learning. Work in progress is also welcome.

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.

Call for abstracts:

In our upcoming call for abstracts, we will be 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 prediction error in
- first and second language acquisition
- learning or processing of acoustic, 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.


Programme committee
Jessie Nixon
Fabian Tomaschek
Harald Baayen





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