32.3828, Confs: Cog Sci, Comp Ling, Gen Ling, Lang Acquisition, Psycholing/Germany

[The LINGUIST List]

LINGUIST List: Vol-32-3828. Wed Dec 08 2021. ISSN: 1069 - 4875.

Subject: 32.3828, Confs: Cog Sci, Comp Ling, Gen Ling, Lang Acquisition, Psycholing/Germany

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Date: Wed, 08 Dec 2021 01:03:18
From: Jessie Nixon [jessie.nixon at uni-tuebingen.de]
Subject: Second International Conference on Error-Driven Learning in Language

 
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: jessie.nixon at uni-tuebingen.de 

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. 

———

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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