Speech-in-speech perception, nonverbal selective attention, and musical training.


Journal

Journal of experimental psychology. Learning, memory, and cognition
ISSN: 1939-1285
Titre abrégé: J Exp Psychol Learn Mem Cogn
Pays: United States
ID NLM: 8207540

Informations de publication

Date de publication:
May 2020
Historique:
pubmed: 4 10 2019
medline: 21 10 2020
entrez: 4 10 2019
Statut: ppublish

Résumé

Speech is more difficult to understand when it is presented concurrently with a distractor speech stream. One source of this difficulty is that competing speech can act as an attentional lure, requiring listeners to exert attentional control to ensure that attention does not drift away from the target. Stronger attentional control may enable listeners to more successfully ignore distracting speech, and so individual differences in selective attention may be one factor driving the ability to perceive speech in complex environments. However, the lack of a paradigm for measuring nonverbal sustained selective attention to sound has made this hypothesis difficult to test. Here we find that individuals who are better able to attend to a stream of tones and respond to occasional repeated sequences while ignoring a distractor tone stream are also better able to perceive speech masked by a single distractor talker. We also find that participants who have undergone more musical training show better performance on both verbal and nonverbal selective attention tasks, and this musician advantage is greater in older participants. This suggests that one source of a potential musician advantage for speech perception in complex environments may be experience or skill in directing and maintaining attention to a single auditory object. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Identifiants

pubmed: 31580123
pii: 2019-58804-001
doi: 10.1037/xlm0000767
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

968-979

Auteurs

Adam Tierney (A)

Department of Psychological Sciences.

Stuart Rosen (S)

Division of Psychology and Language Sciences.

Fred Dick (F)

Department of Psychological Sciences.

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Classifications MeSH