Journal of NeuroscienceNeurosciencePeer-reviewed journal article
Neural representations of non-native speech reflect proficiency and interference from native language knowledge
Christian J. BrodbeckiD, Katerina Danae KandylakiiD, Odette ScharenborgiD
Abstract
Learning to process speech in a foreign language involves learning new representations for mapping the auditory signal to linguistic structure. Behavioral experiments suggest that even listeners that are highly proficient in a non-native language experience interference from representations of their native language. However, much of the evidence for such interference comes from tasks that may inadvertently increase the salience of native language competitors. Here we tested for neural evidence of proficiency and native language interference in a naturalistic story listening task. We studied electroencephalography responses of native Dutch listeners to an English short story, spoken by a native speaker of either American English or Dutch. We modeled brain responses with multivariate temporal response functions, using acoustic and language models. We found evidence for activation of Dutch language statistics when listening to English, but only when it was spoken with a Dutch accent. This suggests that a naturalistic, monolingual setting decreases the interference from native language representations, whereas an accent in the listeners own native language may increase native language interference, by increasing the salience of the native language and activating native language phonetic and lexical representations. Brain responses suggest that words from the native language compete with the foreign language in a single word recognition system, rather than being activated in a parallel lexicon. We further found that secondary acoustic representations of speech (after 200 ms latency) decreased with increasing proficiency. This may reflect improved acoustic-phonetic models in more proficient listeners.
- organism: human
- assay: electronic health records
- research focus: cell type annotation
- approach: statistical model
- Citations
- 11
- FWCI
- 2.84
- Field percentile
- top 9%
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