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Contingent categorisation in speech perception

Overview of attention for article published in Language, Cognition and Neuroscience, August 2013
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Article details
Title
Contingent categorisation in speech perception
Published in
Language, Cognition and Neuroscience, August 2013
DOI 10.1080/01690965.2013.824995
Pubmed ID
Authors
Abstract

The speech signal is notoriously variable, with the same phoneme realized differently depending on factors like talker and phonetic context. Variance in the speech signal has led to a proliferation of theories of how listeners recognize speech. A promising approach, supported by computational modeling studies, is contingent categorization, wherein incoming acoustic cues are computed relative to expectations. We tested contingent encoding empirically. Listeners were asked to categorize fricatives in CV syllables constructed by splicing the fricative from one CV syllable with the vowel from another CV syllable. The two spliced syllables always contained the same fricative, providing consistent bottom-up cues; however on some trials, the vowel and/or talker mismatched between these syllables, giving conflicting contextual information. Listeners were less accurate and slower at identifying the fricatives in mismatching splices. This suggests that listeners rely on context information beyond bottom-up acoustic cues during speech perception, providing support for contingent categorization.

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 48 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
United States 4 8%
United Kingdom 1 2%
Unknown 43 90%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Ph. D. Student 12 25%
Researcher 8 17%
Student > Master 7 15%
Professor 5 10%
Student > Doctoral Student 4 8%
Other 9 19%
Unknown 3 6%
Readers by discipline
Readers by discipline Count As %
Linguistics 14 29%
Psychology 13 27%
Biochemistry, Genetics and Molecular Biology 2 4%
Agricultural and Biological Sciences 2 4%
Neuroscience 2 4%
Other 5 10%
Unknown 10 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 August 2013.
All research outputs
#18,863,806
of 27,362,573 outputs
Outputs from Language, Cognition and Neuroscience
#417
of 640 outputs
Outputs of similar age
#139,012
of 213,684 outputs
Outputs of similar age from Language, Cognition and Neuroscience
#5
of 10 outputs
Altmetric has tracked 27,362,573 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 640 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 213,684 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.