37.3110, Confs: Statistical Learning: From Form to Meaning (United Kingdom)

[The LINGUIST List]

LINGUIST List: Vol-37-3110. Wed Sep 30 2026. ISSN: 1069 - 4875.

Subject: 37.3110, Confs: Statistical Learning: From Form to Meaning (United Kingdom)

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Date: 28-Sep-2026
From: Patrick Rebuschat [p.rebuschat at lancaster.ac.uk]
Subject: Statistical Learning: From Form to Meaning


Statistical Learning: From Form to Meaning
Short Title: SL2027

Date: 28-Jun-2027 - 29-Jun-2027
Location: Lancaster, United Kingdom
Contact: Patrick Rebuschat
Contact Email: language-learning at lancaster.ac.uk
Meeting URL: https://www.lancaster.ac.uk/language-learning/sl2027/

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

Submission Deadline: 18-Jan-2027

We are pleased to announce Statistical Learning: From Form to Meaning,
a two-day conference at Lancaster University, UK, on Monday 28 and
Tuesday 29 June 2027. We invite abstract submissions for talks and
posters.
Statistical learning research has made substantial progress in
explaining how learners detect regularities and acquire structure from
experience. A central remaining question is how these learned patterns
become connected to meaning, and how meaning, in turn, shapes learning
and processing.
We welcome submissions on all aspects of statistical learning across
language, cognition and development. We especially encourage
submissions that address how learners connect patterns in speech,
text, signs and sequences with meaning, including (but not limited
to):
- how meaning shapes the detection of structure, and vice versa
- mapping words and constructions to entities, actions, events and
relations
- cross-situational learning and the integration of linguistic and
non-linguistic information
- the role of communicative intentions, social cues and context in
learning
- the statistics that drive reading, and their link to comprehension
- the role of multimodality in statistical learning
- form-meaning learning in first, second and additional languages,
across the lifespan
- computational, corpus-based, experimental and neuroscientific
approaches to these questions
The programme will include keynote talks, contributed papers, extended
poster sessions and closing discussions, with substantial time for
discussion and interaction.
Invited Speakers:
- Louisa Bogaerts (Ghent University), keynote
- Gabriella Vigliocco (University College London), keynote
- Chen Yu (University of Texas at Austin), keynote
- Ram Frost (Hebrew University of Jerusalem), closing discussant
Abstract Submission:
Abstracts should be submitted via our online form by Monday 18 January
2027, 23:59 anywhere on Earth (AoE):
https://forms.cloud.microsoft/e/ruAbPkJnW6
Further details, including key dates, registration and travel
information, are available on the conference website:
https://www.lancaster.ac.uk/language-learning/sl2027/
For queries, please contact language-learning at lancaster.ac.uk.



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LINGUIST List: Vol-37-3110
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