Links Between Implicit Learning and Spoken Language Processing: Some Preliminary Data

نویسندگان

  • Christopher M. Conway
  • David B. Pisoni
  • Luis Hernandez
چکیده

Spoken language consists of a complex, time-varying signal that contains sequential patterns that can be described in terms of statistical relations among language units. Previous research has suggested that a domain-general ability to learn structured sequential patterns may underlie language acquisition. To test this prediction, we examined the extent to which implicit sequence learning of probabilistically-structured patterns in normal-hearing adults is correlated with performance on a spoken sentence perception task under degraded listening conditions. Our data revealed that performance on the sentence perception task correlated with implicit sequence learning, but only when the sequences were composed of stimuli that were easy to encode verbally. The evidence is consistent with the hypothesis that implicit learning of phonological sequences is an important cognitive ability that contributes to spoken language processing abilities.

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تاریخ انتشار 2008