Literature DB >> 16095588

Perceptual learning for speech: Is there a return to normal?

Tanya Kraljic1, Arthur G Samuel.   

Abstract

Recent work on perceptual learning shows that listeners' phonemic representations dynamically adjust to reflect the speech they hear (Norris, McQueen, & Cutler, 2003). We investigate how the perceptual system makes such adjustments, and what (if anything) causes the representations to return to their pre-perceptual learning settings. Listeners are exposed to a speaker whose pronunciation of a particular sound (either /s/ or /integral/) is ambiguous (e.g., halfway between /s/ and /integral/). After exposure, participants are tested for perceptual learning on two continua that range from /s/ to /integral/, one in the Same voice they heard during exposure, and one in a Different voice. To assess how representations revert to their prior settings, half of Experiment 1's participants were tested immediately after exposure; the other half performed a 25-min silent intervening task. The perceptual learning effect was actually larger after such a delay, indicating that simply allowing time to pass does not cause learning to fade. The remaining experiments investigate different ways that the system might unlearn a person's pronunciations: listeners hear the Same or a Different speaker for 25 min with either: no relevant (i.e., 'good') /s/ or /integral/ input (Experiment 2), one of the relevant inputs (Experiment 3), or both relevant inputs (Experiment 4). The results support a view of phonemic representations as dynamic and flexible, and suggest that they interact with both higher- (e.g., lexical) and lower-level (e.g., acoustic) information in important ways.

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Year:  2005        PMID: 16095588     DOI: 10.1016/j.cogpsych.2005.05.001

Source DB:  PubMed          Journal:  Cogn Psychol        ISSN: 0010-0285            Impact factor:   3.468


  84 in total

1.  Perceptual learning evidence for contextually-specific representations.

Authors:  Tanya Kraljic; Arthur G Samuel
Journal:  Cognition       Date:  2011-09-21

2.  Effects of cross-language voice training on speech perception: whose familiar voices are more intelligible?

Authors:  Susannah V Levi; Stephen J Winters; David B Pisoni
Journal:  J Acoust Soc Am       Date:  2011-12       Impact factor: 1.840

3.  Characteristics of listener sensitivity to talker-specific phonetic detail.

Authors:  Rachel M Theodore; Joanne L Miller
Journal:  J Acoust Soc Am       Date:  2010-10       Impact factor: 1.840

4.  Eye movements reveal fast, voice-specific priming.

Authors:  Megan H Papesh; Stephen D Goldinger; Michael C Hout
Journal:  J Exp Psychol Gen       Date:  2016-01-04

5.  The role of training structure in perceptual learning of accented speech.

Authors:  Christina Y Tzeng; Jessica E D Alexander; Sabrina K Sidaras; Lynne C Nygaard
Journal:  J Exp Psychol Hum Percept Perform       Date:  2016-07-11       Impact factor: 3.332

6.  Developmental Timescale of Rapid Adaptation to Conflicting Cues in Real-Time Sentence Processing.

Authors:  Angele Yazbec; Michael P Kaschak; Arielle Borovsky
Journal:  Cogn Sci       Date:  2019-01

7.  Simultaneous tracking of coevolving distributional regularities in speech.

Authors:  Xujin Zhang; Lori L Holt
Journal:  J Exp Psychol Hum Percept Perform       Date:  2018-10-01       Impact factor: 3.332

8.  Training-induced pattern-specific phonetic adjustments by first and second language listeners.

Authors:  Angela Cooper; Ann Bradlow
Journal:  J Phon       Date:  2018-04-21

9.  Dimension-Based Statistical Learning Affects Both Speech Perception and Production.

Authors:  Matthew Lehet; Lori L Holt
Journal:  Cogn Sci       Date:  2016-09-25

10.  Generalization to unfamiliar talkers in artificial language learning.

Authors:  Sara Finley
Journal:  Psychon Bull Rev       Date:  2013-08
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