Literature DB >> 36076119

Perceptual learning of multiple talkers: Determinants, characteristics, and limitations.

Shawn N Cummings1,2, Rachel M Theodore3,4.   

Abstract

Research suggests that listeners simultaneously update talker-specific generative models to reflect structured phonetic variation. Because past investigations exposed listeners to talkers of different genders, it is unknown whether adaptation is talker specific or rather linked to a broader sociophonetic class. Here, we test determinants of listeners' ability to update and apply talker-specific models for speech perception. In six experiments (n = 480), listeners were first exposed to the speech of two talkers who produced ambiguous fricative energy. The talkers' speech was interleaved during exposure, and lexical context differentially biased interpretation of the ambiguity as either /s/ or /ʃ/ for each talker. At test, listeners categorized tokens from ashi-asi continua, one for each talker. Across conditions and experiments, we manipulated exposure quantity, talker gender, blocked versus interleaved talker structure at test, and the degree to which fricative acoustics differed between talkers. When test was blocked by talker, learning was observed for different but not same gender talkers. When talkers were interleaved at test, learning was observed for both different and same gender talkers, which was attenuated when fricative acoustics were constant across talkers. There was no strong evidence to suggest that adaptation to multiple talkers required increased quantity of exposure beyond that required to adapt to a single talker. These results suggest that perceptual learning for speech is achieved via a mechanism that represents a context-dependent, cumulative integration of experience with speech input and identity critical constraints on listeners' ability to dynamically apply multiple generative models in mixed talker listening environments.
© 2022. The Psychonomic Society, Inc.

Entities:  

Keywords:  Perceptual learning; Speech perception

Mesh:

Year:  2022        PMID: 36076119     DOI: 10.3758/s13414-022-02556-6

Source DB:  PubMed          Journal:  Atten Percept Psychophys        ISSN: 1943-3921            Impact factor:   2.157


  49 in total

1.  Visual recalibration of auditory speech identification: a McGurk aftereffect.

Authors:  Paul Bertelson; Jean Vroomen; Béatrice De Gelder
Journal:  Psychol Sci       Date:  2003-11

2.  Individual talker differences in voice-onset-time.

Authors:  J Sean Allen; Joanne L Miller; David DeSteno
Journal:  J Acoust Soc Am       Date:  2003-01       Impact factor: 1.840

3.  Preliminary results on speaker-dependent variation in the TIMIT database.

Authors:  D Byrd
Journal:  J Acoust Soc Am       Date:  1992-07       Impact factor: 1.840

4.  Effects of talker variability on perceptual learning of dialects.

Authors:  Cynthia G Clopper; David B Pisoni
Journal:  Lang Speech       Date:  2004       Impact factor: 1.500

5.  Time and information in perceptual adaptation to speech.

Authors:  Ja Young Choi; Tyler K Perrachione
Journal:  Cognition       Date:  2019-06-21

6.  Perceptual adaptation to non-native speech.

Authors:  Ann R Bradlow; Tessa Bent
Journal:  Cognition       Date:  2007-05-29

7.  Perception of speech reflects optimal use of probabilistic speech cues.

Authors:  Meghan Clayards; Michael K Tanenhaus; Richard N Aslin; Robert A Jacobs
Journal:  Cognition       Date:  2008-06-25

8.  Lexically guided perceptual tuning of internal phonetic category structure.

Authors:  Julia R Drouin; Rachel M Theodore; Emily B Myers
Journal:  J Acoust Soc Am       Date:  2016-10       Impact factor: 1.840

9.  Lexically guided perceptual learning is robust to task-based changes in listening strategy.

Authors:  Julia R Drouin; Rachel M Theodore
Journal:  J Acoust Soc Am       Date:  2018-08       Impact factor: 1.840

10.  Gorilla in our midst: An online behavioral experiment builder.

Authors:  Alexander L Anwyl-Irvine; Jessica Massonnié; Adam Flitton; Natasha Kirkham; Jo K Evershed
Journal:  Behav Res Methods       Date:  2020-02
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