28.3354, Calls: Cog Sci, Comp Ling, Gen Ling, Pragmatics, Semantics/Germany

[The LINGUIST List]

LINGUIST List: Vol-28-3354. Tue Aug 08 2017. ISSN: 1069 - 4875.

Subject: 28.3354, Calls: Cog Sci, Comp Ling, Gen Ling, Pragmatics, Semantics/Germany

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Date: Tue, 08 Aug 2017 13:10:40
From: Peter Sutton [Peter.Sutton at uni-duesseldorf.de]
Subject: Applications of Probability Theory in Linguistics

 
Full Title: Applications of Probability Theory in Linguistics 
Short Title: APT-Ling 

Date: 08-Mar-2018 - 09-Mar-2018
Location: Stuttgart, Germany 
Contact Person: Peter Sutton
Meeting Email: Peter.Sutton at uni-duesseldorf.de
Web Site: https://sites.google.com/site/aptling2018/home 

Linguistic Field(s): Cognitive Science; Computational Linguistics; General Linguistics; Pragmatics; Semantics 

Call Deadline: 20-Aug-2017 

Meeting Description:

In recent decades, probability theory has been applied to model linguistic
phenomena across a wide range of fields. These include: modelling gradience
and vagueness in semantics (Lassiter & Goodman 2015); a tool for reasoning and
update in pragmatics (Franke & Jäger 2016); in phonology, to model how
stochastic phonetic information can be used to infer phonological categories
(Pierrehumbert 2003); and, as the basis for grammar induction and learning. A
general topic that underlies all of these applications is the formal study of
the relations between noisy, blurred, or underspecified information and the
formation of categorical judgments on the basis of this information, namely,
how concrete judgments regarding the reference of linguistic items can be made
in conditions of uncertainty. Furthermore, should probabilities be represented
as a part of processing or centrally in the grammar itself? Although research
is being conducted across linguistic fields, it is an open question whether
there are similar problems, questions, methods, and solutions that unite the
research of scholars engaged in otherwise seemingly disparate fields of study.
Open questions are: Do we need probability theory to achieve these goals, or
are weaker, more computationally tractable calculi sufficient? What
constraints are there on the use of stochastic reasoning and update processes?
Is the connection between stochastic information and the use and formation of
categorical category judgments describable under a single relation of
reasoning and update?

Targeted Participants:

We aim to bring together scholars from different fields of theoretical and
computational linguistics with the aim of establishing
similarities/differences among different applications of probability theory in
natural language, hence furthering our understanding of the mechanisms and
processes that underpin classification and category formation across a
spectrum of linguistic fields.

Invited Speakers:

- Anton Benz, Leibniz-Zentrum Allgemeine Sprachwissenschaft
- Silke Hamann, University of Amsterdam


2nd Call for Papers:

Abstracts to be submitted via Easychair:
https://easychair.org/conferences/?conf=aptling2018

Please see the conference website for further details:
https://sites.google.com/site/aptling2018/home

Suggested Topics:

Topics for talks include but are not restricted to: 

(i) Similarities and differences among applications of probability theory
different parts of grammar
(ii) Categorical judgements on the basis of probabilistic reasoning and
inference
(iii) Learning of linguistic categories in conditions of uncertainty
(iv) Computational aspects of probability driven classification.




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