Speech recognition software for language learning: Toward an evaluation of validity and student perceptions
DISSERTATION
Deborah Cordier, University of South Florida, United States
University of South Florida . Awarded
Abstract
A renewed focus on foreign language (FL) learning and speech for communication has resulted in computer-assisted language learning (CALL) software developed with Automatic Speech Recognition (ASR). ASR features for FL pronunciation (Lafford, 2004) are functional components of CALL designs used for FL teaching and learning. The ASR features available with the TeLL me More French software provides pronunciation, intonation and speaking practice and feedback. ASR features are examined quantitatively through French student performance of recorded ASR-scored speech and compared with human raters of the same produced speech samples. A comparison of ASR scores to human raters considers the validity of ASR-scored feedback for individualized and FL classroom instruction. Qualitative analyses of student performances and perceptions of ASR are evaluated using an online survey linked to individual pronunciations and performance and examined for positive impact (Chapelle, 2001) and usability.
Citation
Cordier, D. Speech recognition software for language learning: Toward an evaluation of validity and student perceptions. Ph.D. thesis, University of South Florida. Retrieved March 1, 2021 from https://www.learntechlib.org/p/123447/.

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