Creaky voice and utterance fluency measures in predicting perceived fluency and oral proficiency of spontaneous L2 Finnish
Kallio, H., Suviranta, R., Kuronen, M., & Zansen, A. V. (2022). Creaky voice and utterance fluency measures in predicting perceived fluency and oral proficiency of spontaneous L2 Finnish. In S. Frota, M. Cruz, & M. Vigário (Eds.), Speech Prosody 2022 : Proceedings of the 11th International Conference on Speech Prosody (pp. 777-781). International Speech Communication Association. Speech prosody. https://doi.org/10.21437/SpeechProsody.2022-158
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Speech prosodyDate
2022Copyright
© International Speech Communication Association, 2022
While utterance fluency measures are often studied in rela tion to perceived L2 fluency and proficiency, the effect of creaky voice remains ignored. However, creaky voice is frequent in a number of languages, including Finnish, where it serves as a cue for phrase-boundaries and turn-taking. In this study we inves tigate the roles of creaky voice and utterance fluency measures in predicting fluency and proficiency ratings of spontaneous L2 Finnish (F2) speech. In so doing, 16 expert raters participated in assessing narrative spontaneous speech samples from 160 learn ers of Finnish. The effect of creaky voice and utterance fluency measures on proficiency and fluency ratings was studied using linear regression models. The results indicate that creaky voice can contribute to both oral proficiency and fluency alongside utterance fluency measures. Furthermore, average duration of composite breaks – a measure combining breakdown and re pair phenomena – proved to be the most significant predictor of fluency. Based on these findings we recommend further in vestigation of the effect of creaky voice to the assessment of L2 speech as well as reconsideration of the utterance fluency measures used in predicting L2 fluency or proficiency.
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Speech Prosody 2022 : Proceedings of the 11th International Conference on Speech ProsodyISSN Search the Publication Forum
2333-2042Keywords
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https://converis.jyu.fi/converis/portal/detail/Publication/146554995
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Research Council of FinlandFunding program(s)
Academy Project, AoFAdditional information about funding
The DigiTala project is funded by the Academy of Finland and the research consortium includes University of Helsinki (grant number 322619), Aalto University (grant number 322625), and University of Jyväskylä (grant number 322965).License
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