title: A modified statistical pattern recognition approach to measuring the crosslinguistic similarity of Mandarin and English vowels.
abstract: This study describes a statistical approach to measuring crosslinguistic vowel similarity and assesses its efficacy in predicting L2 learner behavior. In the first experiment, using linear discriminant analysis, relevant acoustic variables from vowel productions of L1 Mandarin and L1 English speakers were used to train a statistical pattern recognition model that simultaneously comprised both Mandarin and English vowel categories. The resulting model was then used to determine what categories novel Mandarin and English vowel productions most resembled. The extent to which novel cases were classified as members of a competing language category provided a means for assessing the crosslinguistic similarity of Mandarin and English vowels. In a second experiment, L2 English learners imitated English vowels produced by a native speaker of English. The statistically defined similarity between Mandarin and English vowels quite accurately predicted L2 learner behavior; the English vowel elicitation stimuli deemed most similar to Mandarin vowels were more likely to elicit L2 productions that were recognized as a Mandarin category; English stimuli that were less similar to Mandarin vowels were more likely to elicit L2 productions that were recognized as new or emerging categories.
authors.affiliation: Department of Applied Linguistics, Brock University, St. Catharines, Ontario, Canada. rthomson@brocku.ca
authors.forename: Ron I
authors.initials: RI
authors.lastname: Thomson
authors.forename: Terrance M
authors.initials: TM
authors.lastname: Nearey
authors.forename: Tracey M
authors.initials: TM
authors.lastname: Derwing
mesh_terms: D000293:Adolescent; D000328:Adult; D016002:Discriminant Analysis; D005260:Female; D006801:Humans; D007802:Language; D007858:Learning; D016014:Linear Models; D008037:Linguistics; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D010363:Pattern Recognition, Automated; D046709:Pattern Recognition, Physiological; D010700:Phonetics; D013060:Speech; D013061:Speech Acoustics; D013068:Speech Production Measurement; D055815:Young Adult