2020
DOI: 10.1016/j.jml.2020.104169
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How does dialectal experience modulate anticipatory speech processing?

Abstract: Context-based predictions facilitate speech processing. However, details of predictive processing mechanisms and how factors like language experience shape facilitative processing remain debated. This electroencephalograph study aimed to shed light on these issues by investigating the effect of dialectal experience on lexical prediction. Stimulus sentences were produced in three Mandarin Chinese dialects (home dialect, familiar regional dialect, and unfamiliar regional dialect). Critical nouns varied between s… Show more

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Cited by 14 publications
(12 citation statements)
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“…This is because the failure may be driven by many factors that are external to the research question under investigation: differences in the population and/or language studied, the natural variability in the dependent variable, lab settings, equipment, and protocols can come together to lead to very different outcomes. Indeed, it is possible that when it comes to studying subtle and highly variable aspects of human (IR)REPRODUCIBILITY IN PSYCHOLOGY AND PSYCHOLINGUISTICS (IR)REPRODUCIBILITY IN PSYCHOLOGY AND PSYCHOLINGUISTICS (2020), Brandt et al (2020), Brewer et al (2021), Bristol and Rossano (2020), Brothers and Kuperberg (2021), Brysbaert (2019), Bürki et al (2020), Chan et al (2020), Chetail (2020), Collins et al (2020), Corps and Rabagliati (2020), Dıéez-Álamo et al (2020), Falandays et al (2020), Fellman et al (2020), Floccia et al (2020), Fox et al (2020), Fujita and Cunnings (2020), Gagné et al (2020), Garnham et al (2020), Günther, Nguyen, et al (2020), Günther, Petilli, et al (2020), Hesse and Benz (2020), Hollis (2020), Humphreys et al (2020), Hwang and Shin (2019), Isarida et al (2020), Jäger et al (2020), Johns et al (2020), Kaula and Henson (2020), Lauro et al (2020), Lelonkiewicz et al (2020), Li et al (2020), Liang et al (2021), McKinley and Benjamin (2020),…”
Section: Introductionmentioning
confidence: 99%
“…This is because the failure may be driven by many factors that are external to the research question under investigation: differences in the population and/or language studied, the natural variability in the dependent variable, lab settings, equipment, and protocols can come together to lead to very different outcomes. Indeed, it is possible that when it comes to studying subtle and highly variable aspects of human (IR)REPRODUCIBILITY IN PSYCHOLOGY AND PSYCHOLINGUISTICS (IR)REPRODUCIBILITY IN PSYCHOLOGY AND PSYCHOLINGUISTICS (2020), Brandt et al (2020), Brewer et al (2021), Bristol and Rossano (2020), Brothers and Kuperberg (2021), Brysbaert (2019), Bürki et al (2020), Chan et al (2020), Chetail (2020), Collins et al (2020), Corps and Rabagliati (2020), Dıéez-Álamo et al (2020), Falandays et al (2020), Fellman et al (2020), Floccia et al (2020), Fox et al (2020), Fujita and Cunnings (2020), Gagné et al (2020), Garnham et al (2020), Günther, Nguyen, et al (2020), Günther, Petilli, et al (2020), Hesse and Benz (2020), Hollis (2020), Humphreys et al (2020), Hwang and Shin (2019), Isarida et al (2020), Jäger et al (2020), Johns et al (2020), Kaula and Henson (2020), Lauro et al (2020), Lelonkiewicz et al (2020), Li et al (2020), Liang et al (2021), McKinley and Benjamin (2020),…”
Section: Introductionmentioning
confidence: 99%
“…Efforts have been made to dissociate the contextual facilitation effect due to ease of integration from that due to prediction of an upcoming word, although more recent evidence suggests that both mechanisms may be at play (Nieuwland et al, 2020). Li and colleagues (2020) simultaneously modeled the integration and the prediction processes by measuring ERP responses at transitive verbs in Chinese sentences with SVO (subject-verb-object) order. They found an inverse correlation between the N400 amplitudes at the verbs and the predictability of their following object nouns, which lends strong evidence to the pre-activation effect.…”
Section: Introduction1mentioning
confidence: 99%
“…This analysis could provide good control of the overall type I error rate for comparisons over multiple EEG samples and electrode sites. Meanwhile, this analysis also served as a guide for the selection of spatiotemporal regions of interest (ROIs) for further Linear Mixed Model (LMM) analyses (Luck & Gaspelin, 2017), as previous literature reported different ERP signatures for anticipatory processing of upcoming words (e.g., Li et al, 2020;Otten & Van Berkum, 2009;Wicha et al, 2004). Second, if the permutation tests revealed a significant main (or simple main) effect of Semantic Constraint, group-level LMM analysis was conducted over the single-trial ERP data within the spatiotemporal ROIs in 10-ms steps.…”
Section: Discussionmentioning
confidence: 99%
“…In all LMM models, the acoustic parameters of critical words were also entered to control for potential effects. All VIFs (variance inflation factors) for the predictors were below 1.89, indicating no high multicollinearity in LMM analyses (Li et al, 2020;Zuur et al, 2010). To facilitate model convergence, random correlations between all predictors were removed.…”
Section: Linear Mixed Effects Model Regression Analysismentioning
confidence: 99%