Journal of Digital Contents Society (디지털콘텐츠학회 논문지)

Digital Contents Society (한국디지털콘텐츠학회)
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The Study on Automatic Speech Recognizer Utilizing Mobile Platform on Korean EFL Learners' Pronunciation Development

자동음성인식 기술을 이용한 모바일 기반 발음 교수법과 영어 학습자의 발음 향상에 관한 연구

  • Received : 2017.09.30
  • Accepted : 2017.10.25
  • Published : 2017.10.31
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Abstract

This study explored the effect of ASR-based pronunciation instruction, using a mobile platform, on EFL learners' pronunciation development. Particularly, this quasi-experimental study focused on whether using mobile ASR, which provides voice-to-text feedback, can enhance the perception and production of target English consonants minimal pairs (V-B, R-L, and G-Z) of Korean EFL learners. Three intact classes of 117 Korean university students were assigned to three groups: a) ASR Group: ASR-based pronunciation instruction providing textual feedback by the mobile ASR; b) Conventional Group: conventional face-to-face pronunciation instruction providing individual oral feedback by the instructor; and the c) Hybrid Group: ASR-based pronunciation instruction plus conventional pronunciation instruction. The ANCOVA results showed that the adjusted mean score for pronunciation production post-test on the Hybrid instruction group (M=82.71, SD =3.3) was significantly higher than the Conventional group (M=62.6, SD =4.05) (p<.05).

본 논문은 스마트폰의 플랫폼에 내장되어 있는 자동음성인식 기술을 활용하여 영어 학습자의 발음에 대한 즉각적인 문자 피드백을 제공하는 모바일 기반 발음 교수법이 영어 학습자의 자음 발음 (V-B, R-L, G-Z) 인식과 출력에 미치는 영향에 대해 연구했다. 특히, 자동음성인식 기술을 이용한 모바일 기반 발음 교수법을 사용한 그룹, 전통적인 교사 중심의 발음 교수법 그룹, 그리고 이 둘을 합친 하이브리드 교수법 그룹으로 나누어 영어 학습자의 발음 평가 결과를 (인지, 출력) 비교, 분석했다. ANCOVA를 이용한 분석 결과, 영어 학습자의 발음 출력에 있어 하이브리드 교수법 그룹이 (M=82.71, SD =3.3) 전통적인 교수법 그룹 (M=62.6, SD=4.05) 보다 유의미하게 높은 결과를 나타냈다 (p<.05).

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