Discrimination of uncategorised non-native vowel contrasts is modulated by perceived overlap with native phonological categories. (September 2018)

• Record Type: Journal Article
• Authors: Faris, Mona M.; Best, Catherine T.; Tyler, Michael D.
• Is Part Of: Journal of phonetics. Volume 70(2018)
• Page Start: 1
• Page End: 19
• Publication Date: 2018-09
• Subjects: Cross-language speech perception -- Perceptual assimilation -- Uncategorised assimilations -- Perceived phonological overlap -- Discrimination accuracy -- Vowels; Phonetics -- Periodicals; Phonetics -- Periodicals; Phonétique -- Périodiques; Phonetics; Periodicals; Electronic journals; 414.05
• DOI: 10.1016/j.wocn.2018.05.003
• Languages: English
• ISSNs: 0095-4470

Abstract

Highlights: PAM predictions were evaluated for monophthongal and diphthongal vowel contrasts. Discrimination accuracy was often variable for contrasts of the same assimilation type. Effect of overlap in listeners' L1-assimilations of Uncategorised non-native vowels was examined. The greater the overlap, the less accurately contrasting phones were discriminated. A newly developed measure of overlap accounted for discrimination accuracy. Abstract: Non-native vowels perceived as speech-like but not identified with a particular native (L1) vowel are assimilated as uncategorised, and have received very little empirical attention. According to the Perceptual Assimilation Model (PAM: Best, 1995), contrasts where one or both phones are uncategorised are Uncategorised-Categorised and Uncategorised-Uncategorised, respectively. We reasoned that discrimination accuracy for these assimilations should be influenced by perceived phonological overlap (i.e., overlap in the categorisations to L1 vowels), and predicted excellent discrimination for non-overlapping contrasts, followed by partially overlapping, and completely overlapping contrasts. To test those predictions, Australian English speakers discriminated between Danish monophthongal and diphthongal vowel contrasts that formed Uncategorised-Categorised and Uncategorised-Uncategorised assimilations, varying in the presence of overlap, in addition to Two-Category and Single-Category contrasts. The discrimination accuracy results supported our predictions. These findings have implications for PAM, and broader relevance to second-language learning models, as they allow for more precise discrimination predictions to be made based on assimilation type.