Supporting data for "Expanding Music-to-Language Transfer: Effects of Musicianship on Non-native Lexical Tone Perception, Tone Word Learning, and Native Syntax Comprehension in Cantonese Speakers"

Read full text
Authors: C. C. Ling
Cited by: 0

Abstract

Previous correlational research has documented the advantage of musicianship in lexical tone perception and word learning, leading to the OPERA hypothesis. However, the OPERA hypothesis proposes conditions for music-to-language transfer only at the lower perceptual levels, without explaining whether such musical advantage would apply to higher-level linguistic tasks. Moreover, most previous studies did not consider the heterogeneity of musicianship. Participants were usually classified either as musicians or non-musicians. However, different musical instruments have different demands on auditory perceptual processing (e.g., pitch, rhythm). The differential effects of musicianship types on various perceptual tasks are yet to be explored. To extend the scope of music-to-language transfer research and expand the OPERA hypothesis, this thesis investigates two important issues in non-native and native lexical tone and syntax learning in tone language speakers. Focusing on the effects of musicianship types on non-native lexical tone perception and word learning, Study 1 examines whether Cantonese violinists outperform the pianists and non-musicians on Thai tone discrimination, tone identification, and tone word learning (see Dataset Chapter 3). Focusing on the musical advantage in native syntax learning, Study 2 investigates whether Cantonese musically trained children demonstrate greater musical pitch sensitivity, rhythm sensitivity, and comprehension of Cantonese syntax than the musically untrained children (see Dataset Chapter 4).

Fields of Study & Subjects

Neuroscience and Music Perception Phonetics and Phonology Research Neurobiology of Language and Bilingualism

Publication details

Journal / source
Hong Kong University
Publication date
5 March 2026
Language
EN
Document type
Dataset