Optimizing Auditory Input for Foreign Language Learners Through A Verbotonal-Based Dichotic Listening Approach

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Abstract

Abstract The quality of the physical language signals to which learners are exposed and which result in neurobiological activity leading to perception should be prioritized as it constitutes a variable that is rarely, if ever, considered in language learning. The current study identifies an optimal audio language input signal for Chinese EFL/ESL learners generated by modifying the physical features of language-bearing audio signals. This is achieved by applying the principles of verbotonalism in a dichotic listening context. Low-pass filtered (320 Hz cut-off) and unfiltered speech signals in four different configurations were selectively directed to each hemisphere of the brain through the contralateral ear. The four types of auditory stimuli were: low-pass filtered stimuli in both ears (FL-FR), filtered stimuli in the left ear and unfiltered stimuli in the right ear (FL-R), unfiltered stimuli in the left ear and filtered in the right ear (L-FR), and unfiltered stimuli in both ears (NL-NR). Temporal and spatial neural signatures for the processing of the signals were detected in a combined Event-Related Potential (ERP) and functional Magnetic Resonance Imaging (fMRI) experiment. Results showed that the FL-R configuration provided optimal auditory language input by actively exploiting left-hemispheric dominance for language processing and right-hemispheric dominance for melodic processing, i.e., each hemisphere was fed the signals that it should be best equipped to process and it actually did so effectively. In addition, the L-FR configuration was identified as entirely non-optimal for language learners. Other outcomes included significant load reduction through exposure to FL-FR signals as well as the confirmation that non-language signals were recognized by the brain and did not trigger any language processing. These various outcomes will necessarily entail further research.

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europepmc
last seen: 2026-05-19T01:45:01.086888+00:00
unpaywall
last seen: 2026-05-22T02:00:06.705733+00:00
License: CC-BY-4.0