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No, There Is No 150 ms Lead of Visual Speech on Auditory Speech, but a Range of Audiovisual Asynchronies Varying from Small Audio Lead to Large Audio Lag

Overview of attention for article published in PLoS Computational Biology, July 2014
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Title
No, There Is No 150 ms Lead of Visual Speech on Auditory Speech, but a Range of Audiovisual Asynchronies Varying from Small Audio Lead to Large Audio Lag
Published in
PLoS Computational Biology, July 2014
DOI 10.1371/journal.pcbi.1003743
Pubmed ID
Authors

Jean-Luc Schwartz, Christophe Savariaux

Abstract

An increasing number of neuroscience papers capitalize on the assumption published in this journal that visual speech would be typically 150 ms ahead of auditory speech. It happens that the estimation of audiovisual asynchrony in the reference paper is valid only in very specific cases, for isolated consonant-vowel syllables or at the beginning of a speech utterance, in what we call "preparatory gestures". However, when syllables are chained in sequences, as they are typically in most parts of a natural speech utterance, asynchrony should be defined in a different way. This is what we call "comodulatory gestures" providing auditory and visual events more or less in synchrony. We provide audiovisual data on sequences of plosive-vowel syllables (pa, ta, ka, ba, da, ga, ma, na) showing that audiovisual synchrony is actually rather precise, varying between 20 ms audio lead and 70 ms audio lag. We show how more complex speech material should result in a range typically varying between 40 ms audio lead and 200 ms audio lag, and we discuss how this natural coordination is reflected in the so-called temporal integration window for audiovisual speech perception. Finally we present a toy model of auditory and audiovisual predictive coding, showing that visual lead is actually not necessary for visual prediction.

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The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 1%
United Kingdom 1 1%
United States 1 1%
Germany 1 1%
Unknown 77 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 25 31%
Researcher 21 26%
Student > Master 11 14%
Professor 4 5%
Student > Doctoral Student 4 5%
Other 11 14%
Unknown 5 6%
Readers by discipline Count As %
Psychology 30 37%
Neuroscience 14 17%
Linguistics 8 10%
Computer Science 4 5%
Agricultural and Biological Sciences 3 4%
Other 11 14%
Unknown 11 14%