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LINGUISTIC DIMENSIONS OF COMPREHENSIBILITY AND PERCEIVED FLUENCY: AN INVESTIGATION OF COMPLEXITY, ACCURACY, AND FLUENCY IN SECOND LANGUAGE ARGUMENTATIVE SPEECH

Published online by Cambridge University Press:  27 August 2019

Shungo Suzuki*
Affiliation:
Lancaster University
Judit Kormos
Affiliation:
Lancaster University
*
*Correspondence concerning this article should be addressed to Shungo Suzuki, Lancaster University, Department of Linguistics and English Language, Lancaster, LA1 4YL, United Kingdom. E-mail: s.suzuki@lancaster.ac.uk

Abstract

This study examined the linguistic dimensions of comprehensibility and perceived fluency in the context of L2 argumentative speech elicited from 40 Japanese-speaking learners of English. Their speaking performance was judged by 10 inexperienced native speakers of English for comprehensibility and perceived fluency, and was also objectively analyzed in terms of complexity, accuracy, and fluency as well as pronunciation and discourse features. The results showed that comprehensibility and fluency judgments strongly correlated with each other and that native listeners were significantly more severe when they judged fluency. Furthermore, multiple regression analyses revealed that both constructs were commonly associated with a set of underlying linguistic dimensions (grammatical accuracy, breakdown fluency, and pronunciation). However, comprehensibility was best predicted by articulation rate (speed fluency) whereas perceived fluency was most strongly associated with the frequency of mid-clause pauses (breakdown fluency).

Type
Research Article
Copyright
Copyright © Cambridge University Press 2019 

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Footnotes

We are grateful to Studies in Second Language Acquisition reviewers as well as the journal editor, Susan Gass, and the handling editor, Andrea Révész, for their constructive feedback on earlier versions of the manuscript. We would also like to thank Tetsuo Harada, Kazuya Saito, and J-SLARF members for their helpful comments. Finally, we acknowledge Roy Alderton, Maximilian Topps, and Masaki Eguchi for their help for data analyses.

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