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Cited by 69English Language Learning and TeachingSecond Language Acquisition and LearningEFL/ESL Teaching and Learning

‘Look, I can speak correctly’: learning vocabulary and pronunciation through websites equipped with automatic speech recognition technology

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Bashori, Muzakki, van Hout, Roeland, Strik, Helmer, Cucchiarini, Catia·2024·Computer Assisted Language Learning
DOI 10.1080/09588221.2022.2080230
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Abstract

Speaking skills generally receive little attention in traditional English as a Foreign Language (EFL) classrooms, and this is especially the case in secondary education in Indonesia. A vocabulary deficit and poor pronunciation skills hinder learners in their efforts to improve speaking proficiency. In the present study, we investigated the effects of using two language learning websites, I Love Indonesia (ILI) and NovoLearning (NOVO). These websites are equipped with Automatic Speech Recognition (ASR) technology, with each website providing different types of immediate feedback. We measured written receptive and productive vocabulary knowledge of 40 target words before and after the intervention in which 146 students practiced with these two ASR-based websites, and compared it to that of a control group (n = 86). The ASR-based websites successfully helped students enhance their receptive vocabulary. Twenty-four students participated in a spoken pre-and post-test pronouncing the same 40 target words. We successfully developed an approach to measure pronunciation skills which showed that the treatment groups outperformed the control group. Our results indicate that our technology is successful in improving vocabulary and pronunciation skills.

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  • These findings support previous research on technology as a mediator of vocabulary learning and learner autonomy.

    “These findings support previous research on technology as a mediator of vocabulary learning and learner autonomy (Bashori et al., 2022;Lai & Chen, 2023;Teng, 2022).”

    From Integrating ChatGPT for vocabulary learning and retention: A classroom-based study of Saudi EFL learners (2025) · cites this paper as Bashori et al., 2022

    Section 4.1 reports that students using the ASR-based websites significantly outperformed controls on two receptive-vocabulary tests, supporting the technology-and-vocabulary part of the claim. The Discussion describes personalized training and feedback, but our copy does not establish that the websites improved learner autonomy; the References list a separate work on pronunciation learner autonomy. (LLM, conf=0.86)

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Cited by

Sorted by citations

Authors
Bashori, M., van Hout, R., Strik, H., & Cucchiarini, C.
Affiliations
  • Radboud University Nijmegen (NL)
  • Centre for Language Studies, Radboud University Nijmegen, Nijmegen, The Netherlands
  • Centre for Language and Speech Technology (CLST), Radboud University Nijmegen, Nijmegen, The Netherlands
Corresponding author
Bashori, Muzakki
ORCID
Venue
Computer Assisted Language Learning
Publisher
Informa UK Limited
Published
2022-05-26
Volume
37
Issue
5-6
Pages
1335-1363
ISSN
  • 0958-8221 (ISSN-L)
  • 1744-3210
DOI
10.1080/09588221.2022.2080230
OpenAlex
W4281681798
Cited by
69
References
0
Citations by year
2026: 13 · 2025: 19 · 2024: 23 · 2023: 13 · 2022: 1
FWCI
13.87
Type
journal article
Language
en
Open access
Licence
Locations
  • Computer Assisted Language Learning (publishedVersion, cc-by-nc-nd)
  • Radboud Repository (Radboud University) (submittedVersion)
  • Radboud Repository (Radboud University) (submittedVersion, other-oa)
Topics
  • Physical Sciences › Computer Science › Information Systems › English Language Learning and Teaching
  • Social Sciences › Psychology › Developmental and Educational Psychology › Second Language Acquisition and Learning
  • Social Sciences › Arts and Humanities › Language and Linguistics › EFL/ESL Teaching and Learning
Keywords
speech recognition, vocabulary acquisition, pronunciation skills, English as a foreign language, receptive vocabulary, expressive vocabulary, speaking skills, immediate feedback, pronunciation assessment

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