Literature DB >> 31795676

Acoustic and linguistic factors affecting perceptual dissimilarity judgments of voices.

Tyler K Perrachione1, Kristina T Furbeck1, Emily J Thurston1.   

Abstract

The human voice is a complex acoustic signal that conveys talker identity via individual differences in numerous features, including vocal source acoustics, vocal tract resonances, and dynamic articulations during speech. It remains poorly understood how differences in these features contribute to perceptual dissimilarity of voices and, moreover, whether linguistic differences between listeners and talkers interact during perceptual judgments of voices. Here, native English- and Mandarin-speaking listeners rated the perceptual dissimilarity of voices speaking English or Mandarin from either forward or time-reversed speech. The language spoken by talkers, but not listeners, principally influenced perceptual judgments of voices. Perceptual dissimilarity judgments of voices were always highly correlated between listener groups and forward/time-reversed speech. Representational similarity analyses that explored how acoustic features (fundamental frequency mean and variation, jitter, harmonics-to-noise ratio, speech rate, and formant dispersion) contributed to listeners' perceptual dissimilarity judgments, including how talker- and listener-language affected these relationships, found the largest effects relating to voice pitch. Overall, these data suggest that, while linguistic factors may influence perceptual judgments of voices, the magnitude of such effects tends to be very small. Perceptual judgments of voices by listeners of different native language backgrounds tend to be more alike than different.

Entities:  

Year:  2019        PMID: 31795676      PMCID: PMC7043842          DOI: 10.1121/1.5126697

Source DB:  PubMed          Journal:  J Acoust Soc Am        ISSN: 0001-4966            Impact factor:   1.840


  39 in total

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7.  'Please sort these voice recordings into 2 identities': Effects of task instructions on performance in voice sorting studies.

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Journal:  Br J Psychol       Date:  2019-07-22

8.  Anti-voice adaptation suggests prototype-based coding of voice identity.

Authors:  Marianne Latinus; Pascal Belin
Journal:  Front Psychol       Date:  2011-07-27

9.  Norm-based coding of voice identity in human auditory cortex.

Authors:  Marianne Latinus; Phil McAleer; Patricia E G Bestelmeyer; Pascal Belin
Journal:  Curr Biol       Date:  2013-05-23       Impact factor: 10.834

10.  Representational similarity analysis - connecting the branches of systems neuroscience.

Authors:  Nikolaus Kriegeskorte; Marieke Mur; Peter Bandettini
Journal:  Front Syst Neurosci       Date:  2008-11-24
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  2 in total

1.  Implicit and explicit learning in talker identification.

Authors:  Jayden J Lee; Tyler K Perrachione
Journal:  Atten Percept Psychophys       Date:  2022-05-09       Impact factor: 2.157

2.  Exploring racial and gender disparities in voice biometrics.

Authors:  Xingyu Chen; Zhengxiong Li; Srirangaraj Setlur; Wenyao Xu
Journal:  Sci Rep       Date:  2022-03-08       Impact factor: 4.379

  2 in total

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