Abstract
The article presents an exploratory cross-modal analysis of fluency profiles in spoken and written first (L1, Finnish) and second (L2, English) language production of the same language users. Our data come from two research projects, from which we identified 11 university students participating in both. The spoken tasks consisted of monologue picture description (analysed with Praat), and the written tasks were short argumentative essays (collected and analysed with keystroke logging software GGXLog). Based on commonly used measures to capture different aspects of spoken and written fluency, we used a set of 14 measures (seven for speech fluency, seven for writing fluency) to examine fluency across modes comprehensively. Four profiles were identified from the data: (1) fast and productive, (2) fast, (3) slow and productive, and (4) slow and reflective. Six speakers had the same profile in the L1 and L2, and seven writers had the same profile in the L1 and L2. Only one participant had the same profile in the L1 and L2 speaking and writing. The results suggest that the cross-modal differences are greater than the differences between languages. The modalities are inherently different, which is also reflected in individual variation between the modalities.
Funding source: Research Council of Finland
Award Identifier / Grant number: 331903
Funding source: Koneen Säätiö
Award Identifier / Grant number: 202102802
Acknowledgments
The work was supported by the Research Council of Finland (project Fluency and Disfluency Features in L2 Speech (FDF2), decision number 331903)., and Kone Foundation (project KISUVI, 2022-2026).
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Research ethics: The research follows GDPR regulations.
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Author contributions: The authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Conflict of interest: The authors state no conflict of interest.
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Research funding: Research Council of Finland; Kone Foundation.
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Data availability: The raw data can be obtained on request from the corresponding author.
The following screenshot from the software (GGXLog) illustrates the outputs of the writing process. To learn more about the analyses, see for instance Mutta et al. (sub.).
The screenshot in Figure A.1 illustrates the GGXLog editor window with a progressive graph at the beginning of the text, the written text so far (produced text) and its linear version. This participant makes only a few corrections at this point. In the linear text, the numbers in angle brackets indicate the length of pauses in milliseconds, and in the visualisation, green nodes represent pauses, red nodes insertion of text, and yellow and blue nodes represent removed text and deletion, respectively.

GGXLog editor window with the progressive graph process, the linear text, and the produced text in the beginning of the writing (ID 2010, C1).
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