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A Review on Speech Recognition for Under-Resourced Languages: A Case Study of Vietnamese

Author

Listed:
  • Trung-Nghia Phung

    (Thai Nguyen University of Information and Communication Technology, Vietnam)

  • Duc-Binh Nguyen

    (Thai Nguyen University of Information and Communication Technology, Vietnam)

  • Ngoc-Phuong Pham

    (Thai Nguyen University, Vietnam)

Abstract

Fundamental speech recognition technologies for high-resourced languages are currently successful to build high-quality applications with the use of deep learning models. However, the problem of “borrowing” these speech recognition technologies for under-resourced languages like Vietnamese still has challenges. This study reviews fundamental studies on speech recognition in general as well as speech recognition in Vietnamese, an under-resourced language in particular. Then, it specifies the urgent issues that need current research attention to build Vietnamese speech recognition applications in practice, especially the need to build an open large sentence-labeled speech corpus and open platform for related research, which mostly benefits small individuals/organizations who do not have enough resources.

Suggested Citation

  • Trung-Nghia Phung & Duc-Binh Nguyen & Ngoc-Phuong Pham, 2024. "A Review on Speech Recognition for Under-Resourced Languages: A Case Study of Vietnamese," International Journal of Knowledge and Systems Science (IJKSS), IGI Global, vol. 15(1), pages 1-16, January.
    • Handle: RePEc:igg:jkss00:v:15:y:2024:i:1:p:1-16
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    References listed on IDEAS

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    1. Adem Doganer & Sinan Calik, 2017. "A New Approach Using Hidden Markov Model and Bayesian Method for Estimate of Word Types in Text Mining," International Journal of Knowledge and Systems Science (IJKSS), IGI Global, vol. 8(4), pages 17-29, October.
    2. Tanatorn Tanantong & Monchai Parnkow, 2022. "A Survey of Automatic Text Classification Based on Thai Social Media Data," International Journal of Knowledge and Systems Science (IJKSS), IGI Global, vol. 13(1), pages 1-25, January.
    3. Tessai Hayama & Susumu Kunifuji, 2012. "Information Provision Modules to Support Creation of Slides with Easily Understandable Presentation," International Journal of Knowledge and Systems Science (IJKSS), IGI Global, vol. 3(3), pages 26-41, July.
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