The influence of language-specific properties on the role of consonants and vowels in a statistical learning task of an artificial language: A cross-linguistic comparison

Yaara Lador-Weizman, Avital Deutsch*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The contribution of consonants and vowels in spoken word processing has been widely investigated, and studies have found a phenomenon of a Consonantal bias (C-bias), indicating that consonants carry more weight than vowels. However, across languages, various patterns have been documented, including that of no preference or a reverse pattern of Vowel bias. A central question is how the manifestation of the C-bias is modulated by language-specific factors. This question can be addressed by cross-linguistic studies. Comparing native Hebrew and native English speakers, this study examines the relative importance of transitional probabilities between non-adjacent consonants as opposed to vowels during auditory statistical learning (SL) of an artificial language. Hebrew is interesting because its complex Semitic morphological structure has been found to play a central role in lexical access, allowing us to examine whether morphological properties can modulate the C-bias in early phases of speech perception, namely, word segmentation. As predicted, we found a significant interaction between language and consonant/vowel manipulation, with a higher performance in the consonantal condition than in the vowel condition for Hebrew speakers, namely, C-bias, and no consonant/vowel asymmetry among English speakers. We suggest that the observed interaction is morphologically anchored, indicating that phonological and morphological processes interact during early phases of auditory word perception.

Original languageEnglish
JournalQuarterly Journal of Experimental Psychology
DOIs
StateAccepted/In press - 2024

Bibliographical note

Publisher Copyright:
© Experimental Psychology Society 2024.

Keywords

  • C-bias
  • Hebrew-English cross-linguistic comparison
  • consonants and vowels in speech segmentation
  • statistical learning of an artificial language

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