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A Review on Speech Recognition for Under-Resourced Languages: A Case Study of Vietnamese
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Author(s): Trung-Nghia Phung (Thai Nguyen University of Information and Communication Technology, Vietnam), Duc-Binh Nguyen (Thai Nguyen University of Information and Communication Technology, Vietnam)and Ngoc-Phuong Pham (Thai Nguyen University, Vietnam)
Copyright: 2024
Volume: 15
Issue: 1
Pages: 16
Source title:
International Journal of Knowledge and Systems Science (IJKSS)
Editor(s)-in-Chief: Van Nam Huynh (JAIST, Japan)
DOI: 10.4018/IJKSS.332869
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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.
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