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Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment

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Specificity of dimension-based statistical learning in word recognition.

Kaori Idemaru¹, Lori L Holt²

¹Department of East Asian Languages and Literatures, University of Oregon.

Journal of Experimental Psychology. Human Perception and Performance

|December 25, 2013

Summary

This summary is machine-generated.

Listeners adapt speech perception by statistically learning acoustic cues, like voice-onset time (VOT), based on their context. This learning is specific to the phonetic context and does not automatically generalize across different speech sounds.

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Area of Science:

Psycholinguistics
Auditory Perception
Speech Processing

Background:

Speech perception involves flexible adaptation to ambient speech regularities.
Statistical learning of acoustic dimensions, not fixed values, influences speech categorization.
Understanding how listeners generalize statistical learning across phonetic categories is crucial.

Purpose of the Study:

To investigate dimension-based statistical learning in online word recognition.
To test the generalization of learning across different phonetic categories (place of articulation).
To determine if statistical learning operates obligatorily at the phonological level of stop voicing.

Main Methods:

Listeners performed a word recognition task using voice-onset time (VOT) cues for stop voicing.
Incidental exposure to artificial accents altered the correlation between fundamental frequency (F0) and VOT.
Experiment 1: Assessed learning for bilabial or alveolar rhymes. Experiment 2: Used competing F0/VOT correlations across places of articulation.

Main Results:

Listeners down-weighted reliance on F0 in voicing categorization after exposure to altered F0/VOT correlations, demonstrating dimension-based statistical learning.
Learning was specific to the "accented" phonetic contrast and did not generalize to other places of articulation.
Listeners tracked separate acoustic statistics for different consonant pairs (/b-p/ and /d-t/), indicating context-specific learning.

Conclusions:

Dimension-based statistical learning in speech perception is context-specific.
Listeners can track separate acoustic statistics across different phonetic contexts.
Statistical learning of acoustic cues does not appear to be obligatory at the phonological level of stop voicing.