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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2021.1
- 수록면
- 93 - 104 (12page)
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This study aims to determine how well an automatic speech recognition (ASR) tool could be used in an online EFL course to help L1 Japanese students improve their pronunciation. Previous studies have suggested that ASR tools can be helpful in this regard, but few have dealt with an entirely online course or attempted to use the data to determine which lessons were the most impactful. Therefore, we used a mixture of pre- and posttest data and survey results to determine how students would receive the ASR tool, whether or not they would improve, and what lessons were the most useful to them. The results suggest that students were generally positive towards the ASR-assisted practice and that they quite clearly improved their intelligibility, especially students who began with lower ability. Specifically, the tool was found to be most useful for students who had a lower than 95% accuracy on their pretests. Furthermore, students claimed the tool was most helpful for practicing consonant and vowel sounds, but a statistical model was unable to pinpoint which lessons were most helpful to their overall improvement. Future work should aim to discover the best drills to use and which pronunciation points to teach.
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참고문헌 (26)
참고문헌 신청
Ahn, T. / 2016 / User experience of a mobile speaking application with automatic speech recognition for EFL learning / British Journal of Educational Technology 47(4):778~786
Ashwell, T. / 2017 / How accurately can the Google Web Speech API recognize and transcribe Japanese L2 English learners’ oral production? / JALT CALL Journal 13(1):59~76
Boersma, P / Praat: Doing phonetics by computer
De John, N. H. / 2009 / Praat script to detect syllable nuclei and measure speech rate automatically / Behavior Research Methods 41(2):385~390
Dolman, M. / 2014 / To what extent does musical aptitude influence foreign language pronunciation skills? A multi-factorial analysis of Japanese learners of English / World Journal of English Language 4(4):1~11
Ashwell, T. / 2017 / How accurately can the Google Web Speech API recognize and transcribe Japanese L2 English learners’ oral production? / JALT CALL Journal 13(1):59~76
Boersma, P / Praat: Doing phonetics by computer
De John, N. H. / 2009 / Praat script to detect syllable nuclei and measure speech rate automatically / Behavior Research Methods 41(2):385~390
Dolman, M. / 2014 / To what extent does musical aptitude influence foreign language pronunciation skills? A multi-factorial analysis of Japanese learners of English / World Journal of English Language 4(4):1~11
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