Skip to main content

ETHNOS_APP

Home • Search • Journals • List 0

Learning to understand an unfamiliar talker

Testing distributional learning as a model of rapid adaptive speech perception

Bibliographic Data

ID21306196
AuthorsMaryann Tan (0000-0003-4368-5225, University of Rochester, corresponding author), T Florian Jaeger (0000-0003-1903-7308, University of Rochester)
Year2025
Volume265
Pages106195
Publication date2025-12-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueCognition (JOURNAL)
Journal identifiersISSN: 0010-0277 • E-ISSN: 1873-7838
PublisherElsevier BV (PUBLISHER)
DOI10.1016/j.cognition.2025.106195
PMID40782542
OpenAlexW4413094347
LanguageEN
Citations received1
References cited113

Human speech perception is highly adaptive: exposure to an unfamiliar accent quickly reduces the difficulty listeners might initially experience. How such rapid adaptation unfolds incrementally remains largely unknown. This includes questions about how listeners’ prior expectations based on lifelong experiences are integrated with the unfamiliar speech input, as well as questions about the speed and success of adaptation. We begin to address these knowledge gaps through a combination of an incremental exposure-test paradigm and model-guided data interpretation. We expose US English listeners to shifted phonetic distributions of word-initial “d” and “t” (e.g., “dill” vs. “till”), while incrementally assessing cumulative changes in listeners’ perception. We use Bayesian mixed-effects psychometric models to characterize these changes, and compare listeners’ behavior against both idealized learners (ideal observers that know the exposure statistics) and a model of adaptive speech perception (ideal adaptors that have to infer those statistics). We find that a distributional learning model provides a good qualitative and quantitative fit ( R 2 > 96 % ) to both listeners’ prior perception and changes in their perception depending on the amount and type of exposure. We do, however, also identify previously unrecognized constraints on adaptivity that are unexpected under any existing model of adaptive speech perception: changes in listeners’ perception seem to plateau below the level expected under successful learning

Adaptation (eye) · Cognitive psychology · Perception · Speech perception · Speech recognition · Stress (linguistics) · Computer Science · Linguistic Variation and Morphology · Phonetics and Phonology Research · Psychology · Speech and Audio Processing

  • Online processing of causal and concessive relations in authentic sentences

    Open Access•Markus Frank, Marie-Christin Flohr et al.•Discourse Processes•2026

  • The Timing of Voicing in British English Obstruents

    Gerald J Docherty, Gerard J Docherty•Timing of Voicing in British…•1992

  • Fundamental frequency as an acoustic correlate of stop consonant voicing

    Ralph N Ohde•The Journal of the Acoustical…•1984

  • The Influence of Consonant Environment upon the Secondary Acoustical Characteristics of Vowels

    Arthur S House, Grant Fairbanks•The Journal of the Acoustical…•1953

  • Infant sensitivity to distributional information can affect phonetic discrimination

    Open Access•Jessica Maye, Janet F Werker et al.•Cognition•2002

  • Choosing Prediction Over Explanation in Psychology

    Open Access•Tal Yarkoni, Jacob Westfall•Perspectives on Psychological…•2017

  • Training Japanese listeners to identify English /r/ and /l/

    John S Logan, Scott E Lively et al.•The Journal of the Acoustical…•1991

  • Perceptual adaptation to non-native speech

    Open Access•Ann Bradlow, Ann R Bradlow et al.•Cognition•2008

  • Robust speech perception

    Open Access•Dave F Kleinschmidt, Dave Kleinschmidt et al.•Psychological Review•2015

  • Perceptual learning in speech

    Open Access•Dennis Norris•Cognitive Psychology•2003

  • Echoes of echoes? An episodic theory of lexical access.

    Stephen D Goldinger•Psychological Review•1998

  • Headphone screening to facilitate web-based auditory experiments

    Open Access•Kevin J P Woods, Max H Siegel et al.•Attention, Perception, &…•2017

  • The psychometric function

    Open Access•Felix A Wichmann, N Jeremy Hill•Perception & Psychophysics•2001

  • Rapid adaptation to foreign-accented English

    Constance M Clarke, Merrill F Garrett•The Journal of the Acoustical…•2004

  • Bayesian data analysis for newcomers

    Open Access•John K Kruschke, Torrin M Liddell•Psychonomic Bulletin & Review•2018

  • Generalization in perceptual learning for speech

    Open Access•Tanya Kraljic, A G Samuel•Psychonomic Bulletin & Review•2006

  • Perceptual learning for speech

    Open Access•Tanya Kraljic, A G Samuel•Cognitive Psychology•2005

  • Perception of speech reflects optimal use of probabilistic speech cues

    Open Access•Meghan Clayards, Michael K Tanenhaus et al.•Cognition•2008

  • Transitions, Glides, and Diphthongs

    Ilse Lehiste, Gordon E Peterson•The Journal of the Acoustical…•1961

  • Toward an instance theory of automatization.

    Gordon D Logan•Psychological Review•1988

  • BRMS

    Open Access•Paul-Christian Bürkner•Journal of Statistical Software•2017

  • Categorical data analysis

    Open Access•T Florian Jaeger•Journal of Memory and Language•2008

  • How Computational Modeling Can Force Theory Building in Psychological Science

    Open Access•Olivia Guest, Andrea E Martin•Perspectives on Psychological…•2021

  • A second chance for a first impression

    Open Access•Christina Y Tzeng, Lynne C Nygaard et al.•Psychonomic Bulletin & Review•2021

  • Listeners are initially flexible in updating phonetic beliefs over time

    Open Access•David Saltzman, Emily B Myers et al.•Psychonomic Bulletin & Review•2021

  • More why, less how

    Open Access•Dennis Norris, Antony Cutler et al.•Cognition•2021

  • Encoding and decoding of meaning through structured variability in intonational speech prosody

    Open Access•Xin Xie, Andrés Buxó-Lugo et al.•Cognition•2021

  • Hearing is believing

    Open Access•Shawn N Cummings, Rachel Théodore et al.•Cognition•2023

  • Distributional learning is error-driven

    Paul Olejarczuk, Vsevolod Kapatsinski et al.•Linguistics Vanguard•2018

  • Predictability of stop consonant phonetics across talkers

    Eleanor Chodroff, Camille Wilson et al.•Linguistics Vanguard•2018

  • The influence of perceived L2 sound categories in on-line adaptation and implications for loanword phonology

    Open Access•Yoonjung Kang, Jessamyn Schertz•Natural Language and Linguistic…•2021

  • Caught in the ACT

    Open Access•Simone Mikuteit, Henning Reetz•Language and Speech•2007

  • Structure in talker-specific phonetic realization

    Open Access•Eleanor Chodroff, Camille Wilson et al.•Journal of Phonetics•2017

  • Flexibility and stability of speech sounds

    Open Access•Yi Zheng, A G Samuel•Journal of Phonetics•2023

  • Learning Additional Languages as Hierarchical Probabilistic Inference

    Open Access•Bożena Pająk, Alex B Fine et al.•Language Learning•2016

  • A Cross-Language Study of Voicing in Initial Stops

    Leigh Lisker, Arthur S Abramson•WORD•1964

  • Experimental evidence for expectation-driven linguistic convergence

    Lacey Wade•Language•2022

Unique citing works1
Citations per year1
Citation span2026 - 2026 (1)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 1

Tools

Open DOIOpen Access
Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae