Application of Voice Processing Technology With A Natural Language Processing Approach for Pronunciation Correction of Selected Vocabulary In English
DOI:
https://doi.org/10.55606/jeei.v5i1.3691Keywords:
Speech processing, Natural Language Processing (NLP), Pronunciation correction, English vocabulary, Speaking skillsAbstract
English vocabulary pronunciation is one of the important aspects that must be mastered by English learners. However, many people in Indonesia face difficulties in mastering basic vocabulary pronunciation, which can hinder their progress in the early stages of learning speaking and listening. Mistakes in pronunciation often cause ineffective communication, making the message difficult for the other person to understand. Even at the level of learners who have memorized many vocabularies and are able to have simple conversations, mispronunciation remains a significant obstacle and often hinders smooth communication. To address this challenge, this study aims to develop an application based on speech processing technology and Natural Language Processing (NLP) that is specifically designed to provide pronunciation correction for selected vocabulary. This application focuses on mastering the pronunciation of 500 basic vocabulary as a companion for learning speaking and listening at an early stage. This application does not only aim to memorize vocabulary, but also helps users learn to pronounce each word correctly. With this approach, users can get real-time corrective feedback for each vocabulary spoken, allowing them to correct mistakes directly and gradually improve their speaking ability. In addition, the application provides pronunciation analysis supported by speech processing technology to recognize and analyze user pronunciation errors, while NLP is used to provide relevant assessments and improvement suggestions automatically. The results of the study show that this application is effective in helping learners improve their pronunciation of basic vocabulary. By focusing on frequently used basic vocabulary, this application helps users improve their speaking skills more easily. This application is also a tool that supports independent learning for users, thereby increasing their confidence in speaking English. This study is expected to be a solution that supports more effective and affordable English learning, especially for beginners in Indonesia who want to start mastering speaking and listening with a stronger foundation.
References
[1] M. T. Hidayat, “English Language Proficiency and Career Opportunities: Perceptions of Indonesian University Graduates,” Lang. Value, vol. 17, no. 1, pp. 85–107, Jul. 2024, doi: 10.6035/languagev.7933.
[2] M. H. Al-khresheh, “Phonetic challenges in English: the impact of mispronunciation of the bilabial plosive/p/on communication among Saudi EFL learners,” Cogent Arts Humanit., vol. 11, no. 1, 2024, doi: 10.1080/23311983.2024.2390777.
[3] H. Khoshsima, A. Saed, and S. Moradi, “Computer Assisted Pronunciation Teaching (CAPT) and pedagogy: Improving EFL learners’ pronunciation using Clear Pronunciation 2 software,” Iran. J. Appl. Lang. Stud., vol. 9, no. 1, pp. 98–126, 2017, doi: 10.22111/ijals.2017.3167.
[4] Y. Bu, T. Ma, and W. Li, “Pteacher: A computer-aided personalized pronunciation training system with exaggerated audio-visual corrective feedback,” in Conf. Hum. Factors Comput. Syst. - Proc., 2021. doi: 10.1145/3411764.3445490.
[5] N. Tits and Z. Broisson, “Flowchase: a Mobile Application for Pronunciation Training,” pp. 2–3, 2023, doi: 10.48550/arXiv.2307.0205.
[6] A. H. S. Babekir, “Speech Recognition and Pronunciation Apps and EFL Learners: A Study of Efficacy in Developing Speaking Skills,” Migr. Lett., vol. 20, pp. 883–893, 2023.
[7] A. Puspitasari, A. N. Paradhita, Y. W. Tineka, V. Sulistyowati, N. K. S. Noriska, and Haryanto, “Natural Language Processing (NLP) Technology for Chatbot Website,” J. Penelit. Pendidik. IPA, vol. 10, no. SpecialIssue, pp. 319–324, 2024, doi: 10.29303/jppipa.v10ispecialissue.8241.
[8] A. Mehrish, N. Majumder, R. Bharadwaj, R. Mihalcea, and S. Poria, “A review of deep learning techniques for speech processing,” Inf. Fusion, vol. 99, 2023, doi: 10.1016/j.inffus.2023.101869.
[9] D. Khurana, A. Koli, K. Khatter, and S. Singh, “Natural language processing: state of the art, current trends and challenges,” Multimed. Tools Appl., vol. 82, no. 3, pp. 3713–3744, 2023, doi: 10.1007/s11042-022-13428-4.
[10] Y. Liu, F. binti Ab Rahman, and F. binti Mohamad Zain, “A systematic literature review of research on automatic speech recognition in EFL pronunciation,” Cogent Educ., vol. 12, no. 1, 2025, doi: 10.1080/2331186X.2025.2466288.
[11] H. Ahlawat, N. Aggarwal, and D. Gupta, “Automatic Speech Recognition: A survey of deep learning techniques and approaches,” Int. J. Cogn. Comput. Eng., vol. 6, no. January, pp. 201–237, 2025, doi: 10.1016/j.ijcce.2024.12.007.
[12] A. M. S. Al-Hamzi and L. Musyahda, “Common Errors Identification in Pronouncing Silent Letters in English Words by EFL Novices,” Parol. J. Linguist. Educ., vol. 12, no. 1, pp. 36–49, 2022, doi: 10.14710/parole.v12i1.36-49.
[13] F. Rumaisa, Y. Puspitarani, A. Rosita, A. Zakiah, and S. Violina, “Penerapan Natural Language Processing (NLP) di bidang pendidikan,” J. Inov. Masy., vol. 1, no. 3, pp. 232–235, 2021, doi: 10.33197/jim.vol1.iss3.2021.799.
[14] A. Bapna and others, “mSLAM: Massively multilingual joint pre-training for speech and text,” 2022, [Online]. Available: http://arxiv.org/abs/2202.01374
[15] A. Koenecke, A. S. G. Choi, K. X. Mei, H. Schellmann, and M. Sloane, “Careless Whisper: Speech-to-Text Hallucination Harms,” in 2024 ACM Conf. Fairness, Accountability, Transparency (FAccT 2024), 2024, pp. 1672–1681. doi: 10.1145/3630106.3658996.
[16] A. Andreyev, “Quantization for OpenAI’s Whisper Models: A Comparative Analysis,” 2025, [Online]. Available: http://arxiv.org/abs/2503.09905
[17] A. A. Soni, “Improving Speech Recognition Accuracy Using Custom Language Models with the Vosk Toolkit,” pp. 1–11, 2025, [Online]. Available: http://arxiv.org/abs/2503.21025
[18] S. Magfirah, H. Irsyadi, and N. Fajrhi, “English for Young Learners: Sosialisasi Pentingnya Belajar Bahasa Inggris Sejak Dini di Tingkat Sekolah Dasar,” ADMA J. Pengabdi. dan Pemberdaya. Masy., vol. 4, no. 1, pp. 213–222, 2023, doi: 10.30812/adma.v4i1.3077.
[19] M. Meylina and A. C. Jufri, “Meningkatkan Kosakata Bahasa Inggris Siswa Sekolah Dasar melalui Audio-Lingual Method,” J. Pustaka Mitra, vol. 3, no. 1, pp. 1–7, 2023, doi: 10.55382/jurnalpustakamitra.v3i1.366.
[20] G. A. Grachev, Pareto Principle: Predictable resource concentrations in self-organizing systems. 2024. doi: 10.18522/978-5-9275-4692-3.
[21] A. F. Healy, V. I. Schneider, and J. A. Kole, “Exploring Whether Making Second-Language Vocabulary Learning Difficult Enhances Retention and Transfer,” Behav. Sci., vol. 15, no. 5, 2025, doi: 10.3390/bs15050692.
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