Imitation in a Second Language Relies on Phonological Categories but Does Not Reflect the Productive Usage of Difficult Sound Contrasts.


Journal

Language and speech
ISSN: 1756-6053
Titre abrégé: Lang Speech
Pays: England
ID NLM: 2985214R

Informations de publication

Date de publication:
Sep 2019
Historique:
pubmed: 16 10 2018
medline: 6 2 2020
entrez: 16 10 2018
Statut: ppublish

Résumé

This study investigated the relationship between imitation and both the perception and production abilities of second language (L2) learners for two non-native contrasts differing in their expected degree of difficulty. German learners of English were tested on perceptual categorization, imitation and a word reading task for the difficult English /ɛ/-/æ/ contrast, which tends not to be well encoded in the learners' phonological inventories, and the easy, near-native /i/-/ɪ/ contrast. As expected, within-task comparisons between contrasts revealed more robust perception and better differentiation during production for /i/-/ɪ/ than /ɛ/-/æ/. Imitation also followed this pattern, suggesting that imitation is modulated by the phonological encoding of L2 categories. Moreover, learners' ability to imitate /ɛ/ and /æ/ was related to their perception of that contrast, confirming a tight perception-production link at the phonological level for difficult L2 sound contrasts. However, no relationship was observed between acoustic measures for imitated and read-aloud tokens of /ɛ/ and /æ/. This dissociation is mostly attributed to the influence of inaccurate non-native lexical representations in the word reading task. We conclude that imitation is strongly related to the phonological representation of L2 sound contrasts, but does not need to reflect the learners' productive usage of such non-native distinctions.

Identifiants

pubmed: 30319031
doi: 10.1177/0023830918803978
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

594-622

Auteurs

Miquel Llompart (M)

Ludwig Maximilian University Munich, Germany.

Eva Reinisch (E)

Ludwig Maximilian University Munich, Germany.

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Classifications MeSH