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ERIC Number: EJ1444934
Record Type: Journal
Publication Date: 2024
Pages: 19
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1750-1229
EISSN: EISSN-1750-1237
"I Can Speak": Improving English Pronunciation through Automatic Speech Recognition-Based Language Learning Systems
Muzakki Bashori; Roeland van Hout; Helmer Strik; Catia Cucchiarini
Innovation in Language Learning and Teaching, v18 n5 p443-461 2024
Practicing pronunciation through language learning systems incorporating Automatic Speech Recognition (ASR) technology has been effective in helping improve foreign language pronunciation. One of the ASR affordances is that it can provide immediate, personalized feedback on learners' pronunciation. We investigated the effects of two ASR-based language learning systems, "I Love Indonesia" (ILI) and "NovoLearning" (NOVO), on learners' word-level and sentence-level pronunciation. ILI offers global corrective feedback, while NOVO is equipped with corrective feedback on phonetic details. 117 Indonesian high school students participated in a five-week-long experiment; 52 students used ILI and 65 NOVO. Three pronunciation measures were calculated on a pre and post reading test: phonetic edit distances plus accentedness and comprehensibility ratings. Results indicate significant improvements in learners' pronunciation, confirming that both systems are promising learning tools, with NOVO leading to more progress. Future studies should examine the long-term effects of ASR-based global and phonetic feedback on learners' pronunciation quality.
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Publication Type: Journal Articles; Reports - Research
Education Level: High Schools; Secondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Indonesia
Grant or Contract Numbers: N/A