ArticlePsychonomic bulletin & review2021
A second chance for a first impression: Sensitivity to cumulative input statistics for lexically guided perceptual learning.
Article in Psychonomic bulletin & review, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Apparent Talker Variability and Speaking Style Similarity Can Enhance Comprehension of Novel L2-Accented Talkers.Language and speech · 2026Article
- Speaker effects in language comprehension: An integrative model of language and speaker processing.Psychonomic bulletin & review · 2026Review
- Listeners rapidly adapt to current conditions: "Good-enough" adaptation in multitalker speech perception.Journal of experimental psychology. General · 2025Article
- Language Experience Influences Sociolinguistic Development: The Role of Speaker Race and Language Attitudes on Bilingual and Monolingual Adults' Accent Processing.Brain sciences · 2024Article
- When Jack isn't Jacques: Simultaneous opposite language-specific speech perceptual learning in French-English bilinguals.PNAS nexus · 2024Article
- The Headphone and Loudspeaker Test-Part II: A comprehensive method for playback device screening in Internet experiments.Behavior research methods · 2024Article
- Right Posterior Temporal Cortex Supports Integration of Phonetic and Talker Information.Neurobiology of language (Cambridge, Mass.) · 2023Article
- Rapid but specific perceptual learning partially explains individual differences in the recognition of challenging speech.Scientific reports · 2022Article
- Reliability and validity for perceptual flexibility in speech.Brain and language · 2022Article
- Listeners are initially flexible in updating phonetic beliefs over time.Psychonomic bulletin & review · 2021Article
- Perceptual learning of multiple talkers requires additional exposure.Attention, perception & psychophysics · 2021Article
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Authors and funding
3 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Listeners use lexical knowledge to modify the mapping from acoustics to speech sounds, but the timecourse of experience that informs lexically guided perceptual learning is unknown. Some data suggest that learning is contingent on initial exposure to atypical productions, while other data suggest that learning reflects only the most recent exposure. Here we seek to reconcile these findings by assessing the type and timecourse of exposure that promote robust lexcially guided perceptual learning. In three experiments, listeners (n = 560) heard 20 critical productions interspersed among 200 trials during an exposure phase and then categorized items from an ashi-asi continuum in a test phase. In Experiment 1, critical productions consisted of ambiguous fricatives embedded in either /s/- or /ʃ/-biasing contexts. Learning was observed; the /s/-bias group showed more asi responses compared to the /ʃ/-bias group. In Experiment 2, listeners heard ambiguous and clear productions in a consistent context. Order and lexical bias were manipulated between-subjects, and perceptual learning occurred regardless of the order in which the clear and ambiguous productions were heard. In Experiment 3, listeners heard ambiguous fricatives in both /s/- and /ʃ/-biasing contexts. Order differed between two exposure groups, and no difference between groups was observed at test. Moreover, the results showed a monotonic decrease in learning across experiments, in line with decreasing exposure to stable lexically biasing contexts, and were replicated across novel stimulus sets. In contrast to previous findings showing that either initial or most recent experience are critical for lexically guided perceptual learning, the current results suggest that perceptual learning reflects cumulative experience with a talker's input over time.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.