How acoustic distinctiveness affects spoken word recognition: A pilot study

• Author(s) / Creator(s)

  • Matthew C. Kelley

• In the present study, I propose an acoustically-based alternative to phonological neighborhood density. Phonological neighborhood density has been used in many studies as an approximate quantification of lexical competition during spoken word recognition. However, phonological neighborhood density relies on phonemes, which are divorced from acoustic data, and the method for calculating phonological neighborhood density assigns equal weight to each potential kind of change in the acoustic signal. Moving the quantification of lexical competition into the acoustic domain can mitigate these shortcomings of phonological neighborhood density. I discuss a method of quantifying competition with acoustics, and for a given word, I refer to the result calculating this measure as the word's "acoustic distinctiveness." I then show how this acoustic distinctiveness measure outperforms phonological neighborhood density in modeling participant response times in an auditory lexical decision task. Finally, I conclude with a post-hoc comparison of acoustic distinctiveness and phonological neighborhood density, and then discuss what implications these results have for the mental lexicon. This talk was presented at the 11th International Conference on the Mental Lexicon in Edmonton, AB.

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• Date created

  2018-09-01

• Subjects / Keywords

  • spoken word recognition
  • psycholinguistics
  • linguistics
  • acoustic distance
  • phonetics

• Type of Item

  Conference/Workshop Presentation

• DOI

  https://doi.org/10.7939/R39G5GV9Q

• License

  Attribution-ShareAlike 4.0 International