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Distinguishing underlying and surface variation patterns in speech perception.

Laurel A Lawyer1, David P Corina2

  • 1Department of Linguistics, Center for Mind and Brain, University of California, Davis, 267 Cousteau Drive, Davis, CA 95618, (530) 297-4427 lalawyer@ucdavis.edu.

Language, Cognition and Neuroscience
|March 23, 2019
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Summary
This summary is machine-generated.

Speech perception is influenced by predictable sound variations in English prefixes like "in-" and "un-". Listeners process regular variations more efficiently, impacting word recognition and challenging sparse lexicon theories.

Keywords:
Speech perceptionlexical accessphonologyspeech variationunderspecification

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Area of Science:

  • Psycholinguistics
  • Phonology
  • Cognitive Science

Background:

  • Investigates the link between phonological variation patterns and speech perception.
  • Focuses on English prefixes 'in-'/'im-' and 'un-' which exhibit different variation types.
  • Highlights 'in-' variation due to phonological assimilation and 'un-' surface variation before labial stems.

Purpose of the Study:

  • To determine how predictable phonological variation in prefixes affects speech perception.
  • To test the hypothesis that regularity in variation influences lexical processing.
  • To provide evidence for or against radical underspecification theories of the lexicon.

Main Methods:

  • Employed a go/no-go lexical decision task.
  • Presented subjects with real words and 'mispronounced' stimuli with altered prefix nasals ([n] vs. [m]).
  • Analyzed response times and accuracy for unaltered and altered prefix forms.

Main Results:

  • No significant differences in processing unaltered 'in-' and 'un-' prefixed words.
  • Faster and more accurate responses to 'mispronounced' 'un-' forms compared to 'in-' forms.
  • A significant interaction effect was observed in labial contexts, moderating the difference between prefixes.

Conclusions:

  • Regularity of phonological variation patterns has significant consequences for lexical specification.
  • Findings challenge radical underspecification models advocating for a maximally sparse lexicon.
  • Suggests that predictable variation aids in efficient word recognition and lexical access.