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Speaker Sex Influences Processing of Grammatical Gender

Overview of attention for article published in PLOS ONE, November 2013
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Title
Speaker Sex Influences Processing of Grammatical Gender
Published in
PLOS ONE, November 2013
DOI 10.1371/journal.pone.0079701
Pubmed ID
Authors

Michael S. Vitevitch, Joan Sereno, Allard Jongman, Rutherford Goldstein

Abstract

Spoken words carry linguistic and indexical information to listeners. Abstractionist models of spoken word recognition suggest that indexical information is stripped away in a process called normalization to allow processing of the linguistic message to proceed. In contrast, exemplar models of the lexicon suggest that indexical information is retained in memory, and influences the process of spoken word recognition. In the present study native Spanish listeners heard Spanish words that varied in grammatical gender (masculine, ending in -o, or feminine, ending in -a) produced by either a male or a female speaker. When asked to indicate the grammatical gender of the words, listeners were faster and more accurate when the sex of the speaker "matched" the grammatical gender than when the sex of the speaker and the grammatical gender "mismatched." No such interference was observed when listeners heard the same stimuli, but identified whether the speaker was male or female. This finding suggests that indexical information, in this case the sex of the speaker, influences not just processes associated with word recognition, but also higher-level processes associated with grammatical processing. This result also raises questions regarding the widespread assumption about the cognitive independence and automatic nature of grammatical processes.

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The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Colombia 1 3%
Luxembourg 1 3%
Unknown 35 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 18%
Student > Master 6 16%
Student > Ph. D. Student 6 16%
Student > Bachelor 5 13%
Professor > Associate Professor 2 5%
Other 6 16%
Unknown 6 16%
Readers by discipline Count As %
Linguistics 14 37%
Psychology 6 16%
Social Sciences 3 8%
Computer Science 2 5%
Medicine and Dentistry 2 5%
Other 3 8%
Unknown 8 21%