Listening to the "Noise" in Data

Thursday, 21 Apr 2022 at 7:30 pm – Sun Room, Memorial Union

Listening to the "Noise" in the Data: The Critical Importance of Individual Differences in Second-Language Speech

2022 Quentin Johnson Lecture in Linguistics

Like much other research in the social sciences, studies in applied linguistics often compare the “average” behaviour of groups of language learners on such dimensions as proficiency, fluency and intelligibility. A great deal of attention is devoted to theoretical model-building, in which investigators identify predictive variables that capture L2 learners’ performance as closely as possible. Despite the benefits of that pursuit, researchers often pay insufficient attention to variability in the data that doesn’t readily fit theoretical models, and to treat it as uninteresting noise. In this presentation, I discuss the negative consequences of attending too little to learner differences. Through a review of old and new data, I show that close inspection of individual trajectories in L2 speech acquisition is essential not only to a full understanding of the acquisition process, but also to the development of effective pedagogical practices. This requires more than simply classifying learners into increasingly narrow subgroups.

Dr. Munro completed his Ph.D. under the supervision of Terrance Nearey. He was also a SSHRC Post-doctoral Fellow in James Flege’s speech lab at the University of Alabama in Birmingham. His chief area of interest is Applied Phonetics, with a focus on the perception and production of speech by second language learners. Together with his colleague Tracey Derwing (University of Alberta), he carries out research on speech intelligibility, fluency, foreign accent, and oral language development in Canadian immigrants. Their work has been extensively supported by SSHRC and has appeared in such journals as Applied Linguistics, Journal of Phonetics, Language and Speech, Language Learning, Speech Communication, and Studies in Second Language Acquisition.

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