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The effects of dual-task interference in predicting turn-ends in speech and music
Abstract: Determining when a partner’s spoken or musical turn will end requires well-honed predictive abilities. Evidence suggests that our motor systems are activated during perception of both speech and music, and it has been argued that motor simulation is used to predict turn-ends across domains. Here we used a dual-task interference paradigm to investigate whether motor simulation of our partner’s action underlies our ability to make accurate turn-end predictions in speech and in music. Furthermore, we explored how specific this simulation is to the action being predicted. We conducted two experiments, one investigating speech turn-ends, and one investigating music turn-ends. In each, 34 proficient pianists predicted turn-endings while (1) passively listening, (2) producing an effector-specific motor activity (mouth/hand movement), or (3) producing a task- and effector-specific motor activity (mouthing words/fingering a piano melody). In the speech experiment, any movement during speech perception disrupted predictions of spoken turn-ends, whether the movement was task-specific or not. In the music experiment, only task-specific movement (i.e., fingering a piano melody) disrupted predictions of musical turn-ends. These findings support the use of motor simulation to make turn-end predictions in both speech and music but suggest that the specificity of this simulation may differ between domains.
Keyword: Applied cognition; Language; Motor interference; Music; Prediction; Psychology Research Group; Simulation
URL: http://researchrepository.napier.ac.uk/Output/2787270
https://doi.org/10.1016/j.brainres.2021.147571
https://napier-surface.worktribe.com/2787270/1/The%20Effects%20Of%20Dual-task%20Interference%20In%20Predicting%20Turn-ends%20In%20Speech%20And%20Music%20%28accepted%20version%29
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2
Listeners are better at predicting speakers similar to themselves
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3
Listeners are better at predicting speakers similar to themselves
In: Acta Psychol (Amst) (2020)
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