Abstract

Aims and objectives/purpose/research questions:This study revisits the finding that code-switched language comprehension takes longer than non-switched language.Design/methodology/approach:Using an auditory moving window task, bilinguals operating in single (English) or dual (Spanish–English) language communities listened to sentences presented auditorily. Sentences in Experiments 1a to b were in Spanish and critical targets were either a code-switch or a borrowing, where an English target was pronounced in Spanish. Experiments 2a to b compared code-switched versus non-switched targets within Spanish sentences. Sentences for Experiment 3 were in English with critical targets in Spanish. Context (low/high constraint) and word frequency (low/high) were manipulated.Data and analysis:Data were analyzed using linear mixed effect models ( N = 358), with phonetics (code-switch vs. borrower), context (high- vs. low-constraint), word frequency (high vs. low), and bilingual group (code-switcher vs. English-dominant) as fixed factors, and items and subjects as random factors.Findings/conclusions:Findings from the three experiments suggested that code-switched language results in a processing cost. The bilingual’s linguistic system demands more memory and time to successfully integrate the code-switched information into the sentence. Word frequency and context, as predicted by the featural restriction model, affected the processing of the code-switched targets.Originality:This study is one of the first attempts to investigate bilingual processing employing the auditory moving window technique and the first one to find an interactive effect of context and the type of bilingual and mixed language processing.Significance/implications:The results suggest that there are differences in language switch costs moderated by word frequency, phonetics, and linguistic environment (monolingual vs. bilingual) among bilinguals. The results also suggest that the auditory moving window technique is sensitive to the classic bilingual factors such as code-switching, and other robust psycholinguistic factors such as context and word frequency.

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