The emergence of sub-syllabic representations

Yongeun Lee*, Matthew A Goldrick

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

In a variety of experimental paradigms speakers do not treat all sub-syllabic sequences equally. In languages like English, participants tend to group vowels and codas together to the exclusion of onsets (i.e., /bet/=/b/-/et/). Three possible accounts of these patterns are examined. A hierarchical account attributes these results to the presence of categorical sub-syllabic divisions (e.g., onset /b/ vs. rime /et/). In contrast, a non-hierarchical account attributes these findings to the strength with which particular consonants and vowels co-occur (e.g., the relative frequency of /be/ vs. /et/). A third emergentist alternative is articulated, where speakers' knowledge is sensitive not just to the frequency with which particular segments co-occur but also to the general patterns of association within a language. These accounts are contrasted by examining sub-syllabic patterns in two languages: Korean and English. A statistical study shows distinctions in the general patterns of sub-syllabic associations in Korean and English. Consistent with the emergentist perspective, results of short-term memory experiments reveal that Korean and English speakers are sensitive not only to these general patterns but also to the strength with which particular segment sequences are associated. The implications of these results for theories of sub-syllabic patterns in languages are discussed.

Original languageEnglish (US)
Pages (from-to)155-168
Number of pages14
JournalJournal of Memory and Language
Volume59
Issue number2
DOIs
StatePublished - Aug 1 2008

Keywords

  • Phonotactic probability
  • Short-term memory tests
  • Sub-syllabic constituents

ASJC Scopus subject areas

  • Neuropsychology and Physiological Psychology
  • Language and Linguistics
  • Experimental and Cognitive Psychology
  • Linguistics and Language
  • Artificial Intelligence

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