36.2036, Confs: Workshop on The Role of Representation in Computational Phonology (United Kingdom)

Wed Jul 2 09:05:02 UTC 2025

LINGUIST List: Vol-36-2036. Wed Jul 02 2025. ISSN: 1069 - 4875.

Subject: 36.2036, Confs: Workshop on The Role of Representation in Computational Phonology (United Kingdom)

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Date: 01-Jul-2025
From: Andrew Lamont [andrew.lamont at ucl.ac.uk]
Subject: Workshop on The Role of Representation in Computational Phonology

Workshop on The Role of Representation in Computational Phonology

Date: 13-Jan-2026 - 13-Jan-2026
Location: Cambridge, United Kingdom
Contact: Andrew Lamont
Contact Email: andrew.lamont at ucl.ac.uk
Meeting URL: https://www.phonetics.mmll.cam.ac.uk/ocp23/representation

Linguistic Field(s): Computational Linguistics; Phonology

Submission Deadline: 01-Aug-2025

We are pleased to announce the OCP23 Satellite Workshop on The Role of
Representation in Computational Phonology to be held on 13 January at
the University of Cambridge.
Phonological representations minimally assume linearly ordered
elements, and have been augmented to include hierarchical structure
like prosodic categories and non-linear structure like autosegmental
tiers. McCarthy’s (1988:84) often quoted adage, “if the
representations are right, then the rules will follow” implies the
analytic advantage of representations other than strings. This
workshop explores their computational consequences.
To give an illustrative example, Slovenian bans [+anterior] stridents
before [−anterior] stridents, Slovenian bans [+anterior] stridents
before [−anterior] stridents, e.g., [sl-ux] ‘hearing’ [ʃl-iʃ-i]
*[sl-iʃ-i] ‘hears’ (Jurgec, 2011:330). This can be modeled by
projecting a tier of stridents and banning adjacent segments that
disagree in the feature [anterior], e.g., [ʃl-iʃ-i] → [ʃʃ], *[sl-iʃ-i]
→ *[sʃ]. This approach straightforwardly captures blocking effects by
intervening coronal stops, e.g., [sit] ‘full’ [na-sit-iʃ] ‘(you) feed’
(Jurgec, 2011:331), by projecting them onto the tier: [na-sit-iʃ] →
[stʃ]. Unsurprisingly, strident affricates participate in harmony,
e.g., [ʦepəʦ] ‘foot’ [ʧepʧək] ‘fool-DIM’ (Jurgec, 2011:330). However,
if affricates were interpreted as clusters, it would not be possible
to model these alternations by banning strings on a projected tier,
illustrating an interaction between phonological representations and
computational complexity (see Lamont, 2023 for more examples along
these lines). Previous work has shown that adopting autosegmental
representations reduces the complexity of tonotactics (Jardine, 2016)
and that adopting feet reduces the complexity of stress (Koser, 2022),
providing computational support for these representations.
We invite abstracts for workshop talks on the role representations
from traditional phonological theory play in computational phonology
and how computational approaches can inform traditional views of
representation. Topics may include, but are not limited to:
- Phenomena whose analyses are made simpler/more complex by adopting
different representations
- The role of learnability (e.g., Gouskova and Stanton, 2021; Lee et
al., 2023) and what structures should/must be encoded in UG
- Equivalences between different representations (e.g.,
Strother-Garcia, 2019; Jardine et al., 2021)
We especially encourage submissions that discuss novel data sets
and/or representations that are not widely assumed in the phonological
literature. Submissions do not need to be couched in model
theory/formal language theory; we invite perspectives from various
theoretical backgrounds.
Please submit anonymous abstracts using the link below by August 1.
Please do not use more than two pages for content; you may use
additional pages for references, tables, and figures (within reason).
We aim to notify authors of our decisions in September. If you have
any questions, please contact Andrew Lamont.
https://openreview.net/group?id=OCP/2026/Workshop/Role_of_Representation_in_Computational_Phonology
References:
Gouskova, Maria and Juliet Stanton (2021). Learning complex segments.
Language 97(1). 151–193.
Jardine, Adam (2016). Locality and non-linear representations in tonal
phonology. Ph.D. dissertation, University of Delaware.
Jardine, Adam, Nick Danis and Luca Iacoponi (2021). A formal
investigation of Q-Theory in comparison to Autosegmental
Representations. Linguistic Inquiry 52(2). 333–358.
Jurgec, Peter (2011). Feature spreading 2.0: A unified theory of
assimilation. Ph.D. dissertation, University of Tromsø.
Koser, Nate (2022). The computational nature of stress assignment.
Ph.D. dissertation, Rutgers, The State University of New Jersey.
Lamont, Andrew (2023). Phonotactics conspire to reduce computational
complexity. Unpublished manuscript, University College London.
Available at https://aphonologist.github.io/papers.
Lee, Seung Suk, Alessa Farinella, Cerys Hughes and Joe Pater (2023).
Learning stress with feet and grids. In Noah Elkins, Bruce Hayes,
Jinyoung Jo and Jian-Leat Siah (eds.), Proceedings of the 2022 Annual
Meeting on Phonology. Washington, D.C.: Linguistic Society of America.
https://doi.org/10.3765/amp.v10i0.5441.
McCarthy, John J. (1988). Feature geometry and dependency: A review.
Phonetica 45. 84–108.
Strother-Garcia, Kristina (2019). Using model theory in phonology: A
novel characterization of syllable structure and syllabification.
Ph.D. dissertation, University of Delaware.

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