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Recommending the Workflow of Vietnamese Sign Language Translation via a Comparison of Several Classification Algorithms

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Computational Linguistics (PACLING 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1215))

Abstract

The Vietnamese deaf community communicates via a special language called Vietnamese Sign Language (VSL). Three-dimensional space and hand gesture are primarily used to convey meanings that allow deaf people to communicate among themselves and with non-deaf people around them. It maintains syntax, grammar, and vocabulary which is completely different from regular spoken and/or written Vietnamese. The normal procedure of transformation from spoken and/or written language (SWL) to VSL consists of consecutive steps: (i) Vietnamese word tokenization, (ii) machine translation into written sign language sentences, and (iii) conversion of these written sign language sentences into visual sign gesture. In this procedure, the second step gets the most attention due to the completion of the conveyed message. The basic challenge is that sign language, in general, has limited vocabulary compared to spoken/written language. If the machine translation is poorly performed, the complete message might not be successfully communicated, or in some cases, the conveyed message has a different meaning from the original. Consequently, the high accuracy translation should be maintained in any circumstances. This research is the efforts of evaluating an effective classification algorithm that the authors recommend to be integrated into the workflow of VSL translation. We believe that this is the first showing a quantitative comparison of several classification algorithms used in the workflow. The experimental results show that the translation accuracy rate is 96.7% which strongly support our recommendation.

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Notes

  1. 1.

    https://github.com/raianrido/VSL.

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Acknowledgment

Many thanks to the MOET’s Research Project named “A study of proposing a solution to translate TV’s News into 3D sign language animations for the deaf”, project code no.: B2013-16-31, for funding this study. The authors would like to thank the Center for Research and Education of the Deaf and Hard of Hearing for supporting this study.

Author information

Authors and Affiliations

  1. FPT University, Can Tho City, Vietnam

    Luyl-Da Quach & Nghia Duong-Trung

  2. Korea Advanced Institute of Science and Technology, Daejeon, South Korea

    Anh-Van Vu

  3. Can Tho University, Can Tho City, Vietnam

    Chi-Ngon Nguyen

Authors
  1. Luyl-Da Quach
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  2. Nghia Duong-Trung
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  3. Anh-Van Vu
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  4. Chi-Ngon Nguyen
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Corresponding author

Correspondence to Chi-Ngon Nguyen .

Editor information

Editors and Affiliations

  1. Japan Advanced Institute of Science and Technology, Ishikawa, Japan

    Le-Minh Nguyen

  2. University of Engineering and Technology, Hanoi, Vietnam

    Xuan-Hieu Phan

  3. Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan

    Kôiti Hasida

  4. Japan Advanced Institute of Science and Technology, Ishikawa, Japan

    Satoshi Tojo

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Quach, LD., Duong-Trung, N., Vu, AV., Nguyen, CN. (2020). Recommending the Workflow of Vietnamese Sign Language Translation via a Comparison of Several Classification Algorithms. In: Nguyen, LM., Phan, XH., Hasida, K., Tojo, S. (eds) Computational Linguistics. PACLING 2019. Communications in Computer and Information Science, vol 1215. Springer, Singapore. https://doi.org/10.1007/978-981-15-6168-9_12

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  • DOI: https://doi.org/10.1007/978-981-15-6168-9_12

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-6167-2

  • Online ISBN: 978-981-15-6168-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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