Volume 71, Issue 3 pp. 626-668
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The Effect of Speaker Proficiency on Intelligibility, Comprehensibility, and Accentedness in L2 Spanish: A Conceptual Replication and Extension of Munro and Derwing (1995a)

Amanda Huensch

Corresponding Author

Amanda Huensch

University of Pittsburgh

Correspondence concerning this article should be addressed to Amanda Huensch, Department of Linguistics, University of Pittsburgh, 2816 Cathedral of Learning, Pittsburgh, PA 15260, USA, E-mail: [email protected]

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Charlie Nagle
First published: 30 March 2021
Citations: 20

This work was funded by a University of South Florida Creative Scholarship Grant and by a University of South Florida Nexus Initiative Award to the first author and by an Iowa State University Social Sciences Seed Grant to the second author. We would like to thank the participants and our research assistants, especially Aneesa Ali and Bianca Pinkerton. We would also like to thank Joseph Casillas for his help with some of the statistical analyses reported in this paper.

The handling editor for this article was Emma Marsden.

Abstract

This study investigated the relationship among intelligibility, comprehensibility, and accentedness in the speech of second language learners of Spanish of varying proficiency in instructed contexts. It conceptually replicated studies by Munro and Derwing (1995a) and Derwing and Munro (1997), who found partial independence among the three speech dimensions but also evidence that proficiency may mediate the relationship between linguistic features of stimuli (e.g., phonemic and grammatical error rates) and speech dimensions. Speech data from 42 second language learners of Spanish recruited from two different universities were elicited via a semispontaneous speaking task: the picture-based narration from the initial study. Amazon Mechanical Turk was used to recruit 80 native Spanish listeners to transcribe and rate extracted utterances. The utterances were coded for grammatical and phonemic errors, goodness of prosody, and speaking rate. Analyses included mixed-effects models that allowed estimation of individual variation across facets of the data, particularly those of listeners.

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