36.2639, Confs: Deep Phonology: Doing Phonology With Deep Learning (AMP 2025 Special Session) (USA)

Thu Sep 4 12:05:02 UTC 2025

LINGUIST List: Vol-36-2639. Thu Sep 04 2025. ISSN: 1069 - 4875.

Subject: 36.2639, Confs: Deep Phonology: Doing Phonology With Deep Learning (AMP 2025 Special Session) (USA)

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================================================================

Date: 03-Sep-2025
From: Gasper Begus [begus at berkeley.edu]
Subject: Deep Phonology: Doing Phonology With Deep Learning (AMP 2025 Special Session)

Deep Phonology: Doing Phonology With Deep Learning (AMP 2025 Special
Session)

Date: 27-Sep-2025 - 27-Sep-2025
Location: Berkeley, California, USA
Contact: Gasper Begus
Contact Email: begus at berkeley.edu
Meeting URL:
https://sites.google.com/berkeley.edu/amp2025/special-session

Linguistic Field(s): Computational Linguistics; Language Acquisition;
Phonetics; Phonology

On Saturday, September 27, 2025, following the main AMP session held
on September 25-26, 2025, there will be a special session on "Deep
Phonology: Doing phonology with deep learning" held on the UC Berkeley
campus.
Phonology has been modeled using rules, constraints, finite state
machines, exemplars, and many other approaches. Recent advances in
deep learning have prompted researchers to explore how deep neural
architectures (e.g., seq2seq models, transformers, RNNs, LSTMs, VAEs,
GANs) can shed new light on human sound systems. This workshop aims to
bring together scholars who use—or are interested in—deep learning to
model phonological processes and phenomena.
AMP 2025 Special Session: Deep Phonology
Time and venue: September 27, 2025, Dwinelle 370, UC Berkeley
Program
09:00 - 09:30  "AI-assisted analysis of phonological variation in
English"
               Authors: Virginia Partridge (UMass Amherst); Joe Pater
(UMass Amherst);
                        Parth Bhangla (UMass Amherst); Ali Nirheche
(UMass Amherst);
                        Brandon Prickett (UMass Amherst)
09:30 - 10:00  "Comparing Phonological Feature Sets for Low-Resource
ASR"
               Authors: Alessio Tosolini (Yale); Massimo Daul (NYU);
Ayla Karakas (Yale); Claire Bowern (Yale)
10:00 - 10:15  Break
10:15 - 10:45  "Can large language models predict English phrasal
stress?"
               Authors: Jinyoung Jo (Stanford); Sean Choi (Santa Clara
U);
                        Arto Anttila (Stanford)
10:45 - 11:15  "Emergent morpho-phonological patterning in a model of
spoken word recognition"
               Authors: Jon Gauthier (UCSF); Matthew Leonard (UCSF);
Edward Chang (UCSF)
11:15 - 12:15  POSTER SESSION (see list below)
12:15 - 13:15  Lunch
13:15 - 14:45  PLENARY: "Modeling language acquisition as speech
development"
               Speaker: Stephan Meylan (UC Berkeley)
14:45 - 15:00  Break
15:00 - 15:30  "Modeling Prosodic Development with Prenatal Audio
Attenuation"
               Authors: Frank Li Hui Tan (HKU); Shuang Zheng (HKU);
                        Ming Liu (HKU); Youngah Do (HKU)
15:30 - 16:00  "Evaluating Wasserstein GAN discriminators as models of
human well-formedness judgments"
               Author:  Bruno Ferenc Segedin (Brown)
16:00 - 16:45  PANEL DISCUSSION: Future Directions in Deep Phonology
               Panelists: Youngah Do; Volya Kapatsinski; Joe Pater;
Mike Hammond; Jason Shaw
Poster Session (11:15 - 12:15)
1. Phonological Feature Probing for Accent Discrimination in SSL
Representations (virtual)
   Authors: Nitin Venkateswaran (U of Florida); Ratree Wayland (U
Florida);
            Kevin Tang (Heinrich Heine U)
2. Vowel length contrasts in deep learning: Generative Adversarial
Phonology and duration
   Author: Wing-sze KAT (Chinese U of Hong Kong)
3. Sub-regular inductive biases in a phonological transformer
(virtual)
   Authors: Micha Elsner (The Ohio State); Stu Black (Independent
Researcher)
4. Shallow models, deep insights: gradient phonological preferences in
Polish yer alternations
   Author: Maria Bolek (U of Warsaw)
5. Exploring Lexical Variation of Italian Mid Vowel Targets using the
Neural Network Phonet
   Authors: Austin Jones (U of Georgia); Margaret E. L. Renwick (U of
Georgia, JHU)
6. Phone2Vec
   Author: Michael Hammond (U of Arizona)
7. Emergent feature structure in self-supervised speech models' phone
representations
   Authors: Canaan Breiss (USC); Jon Gauthier (UCSF)
8. The processing of neutral tone in self-supervised learning speech
models
   Author: Chenzi Xu (Oxford)
We are proudly supported by the Institute of Cognitive and Brain
Sciences at UC Berkeley.

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