Rule-Based Machine Translation for the Automatic Translation of Vietnamese Sign Language

Thi-Bich-Diep Nguyen; Thi-Tam Nguyen

doi:doi:10.11648/j.ijll.20231106.12

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Rule-Based Machine Translation for the Automatic Translation of Vietnamese Sign Language

Thi-Bich-Diep Nguyen, Thi-Tam Nguyen

Published in International Journal of Language and Linguistics (Volume 11, Issue 6)

Received: 6 November 2023 Accepted: 8 December 2023 Published: 18 December 2023

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Abstract

Sign language is acknowledged as a unique language in the field of machine translation, possessing distinct grammatical characteristics compared to written or spoken Vietnamese. These include simplifications, altered word order, and emphasis on stress. This article explores a rule-based machine translation approach specifically designed to translate Vietnamese utterances into grammatically accurate Vietnamese Sign Language sentences. While considered a conventional technique, this approach demonstrates remarkable success in this specific scenario. Evaluation results reveal that the proposed method outperforms several contemporary machine translation models for this particular challenge, achieving a BLEU score of 62.55. This achievement is particularly noteworthy considering the limited resources available for Vietnamese Sign Language. Moreover, experiments conducted with varying data sizes further solidify the effectiveness of this method within a defined domain. Notably, the BLEU score surpasses expectations for typical translation problems, highlighting the effectiveness of both the probabilistic model and the intuitive linguistic model employed. This study demonstrates the potential of rule-based machine translation for Vietnamese Sign Language, particularly in situations where resources are limited. The encouraging results pave the way for further research and development in this area, ultimately aiming to improve communication and accessibility for the Vietnamese deaf community.

Published in	International Journal of Language and Linguistics (Volume 11, Issue 6)
DOI	10.11648/j.ijll.20231106.12
Page(s)	191-198
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2023. Published by Science Publishing Group

Keywords

Natural Language Processing, Machine Translation, Rule-Based, Low-Resource Language, Sign Language

References

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Cite This Article

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APA Style

Nguyen, T., Nguyen, T. (2023). Rule-Based Machine Translation for the Automatic Translation of Vietnamese Sign Language. International Journal of Language and Linguistics, 11(6), 191-198. https://doi.org/10.11648/j.ijll.20231106.12

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ACS Style

Nguyen, T.; Nguyen, T. Rule-Based Machine Translation for the Automatic Translation of Vietnamese Sign Language. Int. J. Lang. Linguist. 2023, 11(6), 191-198. doi: 10.11648/j.ijll.20231106.12

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AMA Style

Nguyen T, Nguyen T. Rule-Based Machine Translation for the Automatic Translation of Vietnamese Sign Language. Int J Lang Linguist. 2023;11(6):191-198. doi: 10.11648/j.ijll.20231106.12

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@article{10.11648/j.ijll.20231106.12,
  author = {Thi-Bich-Diep Nguyen and Thi-Tam Nguyen},
  title = {Rule-Based Machine Translation for the Automatic Translation of Vietnamese Sign Language},
  journal = {International Journal of Language and Linguistics},
  volume = {11},
  number = {6},
  pages = {191-198},
  doi = {10.11648/j.ijll.20231106.12},
  url = {https://doi.org/10.11648/j.ijll.20231106.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijll.20231106.12},
  abstract = {Sign language is acknowledged as a unique language in the field of machine translation, possessing distinct grammatical characteristics compared to written or spoken Vietnamese. These include simplifications, altered word order, and emphasis on stress. This article explores a rule-based machine translation approach specifically designed to translate Vietnamese utterances into grammatically accurate Vietnamese Sign Language sentences. While considered a conventional technique, this approach demonstrates remarkable success in this specific scenario. Evaluation results reveal that the proposed method outperforms several contemporary machine translation models for this particular challenge, achieving a BLEU score of 62.55. This achievement is particularly noteworthy considering the limited resources available for Vietnamese Sign Language. Moreover, experiments conducted with varying data sizes further solidify the effectiveness of this method within a defined domain. Notably, the BLEU score surpasses expectations for typical translation problems, highlighting the effectiveness of both the probabilistic model and the intuitive linguistic model employed. This study demonstrates the potential of rule-based machine translation for Vietnamese Sign Language, particularly in situations where resources are limited. The encouraging results pave the way for further research and development in this area, ultimately aiming to improve communication and accessibility for the Vietnamese deaf community.
},
 year = {2023}
}

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TY  - JOUR
T1  - Rule-Based Machine Translation for the Automatic Translation of Vietnamese Sign Language
AU  - Thi-Bich-Diep Nguyen
AU  - Thi-Tam Nguyen
Y1  - 2023/12/18
PY  - 2023
N1  - https://doi.org/10.11648/j.ijll.20231106.12
DO  - 10.11648/j.ijll.20231106.12
T2  - International Journal of Language and Linguistics
JF  - International Journal of Language and Linguistics
JO  - International Journal of Language and Linguistics
SP  - 191
EP  - 198
PB  - Science Publishing Group
SN  - 2330-0221
UR  - https://doi.org/10.11648/j.ijll.20231106.12
AB  - Sign language is acknowledged as a unique language in the field of machine translation, possessing distinct grammatical characteristics compared to written or spoken Vietnamese. These include simplifications, altered word order, and emphasis on stress. This article explores a rule-based machine translation approach specifically designed to translate Vietnamese utterances into grammatically accurate Vietnamese Sign Language sentences. While considered a conventional technique, this approach demonstrates remarkable success in this specific scenario. Evaluation results reveal that the proposed method outperforms several contemporary machine translation models for this particular challenge, achieving a BLEU score of 62.55. This achievement is particularly noteworthy considering the limited resources available for Vietnamese Sign Language. Moreover, experiments conducted with varying data sizes further solidify the effectiveness of this method within a defined domain. Notably, the BLEU score surpasses expectations for typical translation problems, highlighting the effectiveness of both the probabilistic model and the intuitive linguistic model employed. This study demonstrates the potential of rule-based machine translation for Vietnamese Sign Language, particularly in situations where resources are limited. The encouraging results pave the way for further research and development in this area, ultimately aiming to improve communication and accessibility for the Vietnamese deaf community.

VL  - 11
IS  - 6
ER  -

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Author Information

Thi-Bich-Diep Nguyen

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

Contact Email
Thi-Tam Nguyen

Department of Electronics and Informatics, College of Industrial Techniques (CIT), Bac Giang, Vietnam

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Plain Text BibTeX RIS

APA Style

Nguyen, T., Nguyen, T. (2023). Rule-Based Machine Translation for the Automatic Translation of Vietnamese Sign Language. International Journal of Language and Linguistics, 11(6), 191-198. https://doi.org/10.11648/j.ijll.20231106.12

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ACS Style

Nguyen, T.; Nguyen, T. Rule-Based Machine Translation for the Automatic Translation of Vietnamese Sign Language. Int. J. Lang. Linguist. 2023, 11(6), 191-198. doi: 10.11648/j.ijll.20231106.12

Copy | Download

AMA Style

Nguyen T, Nguyen T. Rule-Based Machine Translation for the Automatic Translation of Vietnamese Sign Language. Int J Lang Linguist. 2023;11(6):191-198. doi: 10.11648/j.ijll.20231106.12

Copy | Download

@article{10.11648/j.ijll.20231106.12,
  author = {Thi-Bich-Diep Nguyen and Thi-Tam Nguyen},
  title = {Rule-Based Machine Translation for the Automatic Translation of Vietnamese Sign Language},
  journal = {International Journal of Language and Linguistics},
  volume = {11},
  number = {6},
  pages = {191-198},
  doi = {10.11648/j.ijll.20231106.12},
  url = {https://doi.org/10.11648/j.ijll.20231106.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijll.20231106.12},
  abstract = {Sign language is acknowledged as a unique language in the field of machine translation, possessing distinct grammatical characteristics compared to written or spoken Vietnamese. These include simplifications, altered word order, and emphasis on stress. This article explores a rule-based machine translation approach specifically designed to translate Vietnamese utterances into grammatically accurate Vietnamese Sign Language sentences. While considered a conventional technique, this approach demonstrates remarkable success in this specific scenario. Evaluation results reveal that the proposed method outperforms several contemporary machine translation models for this particular challenge, achieving a BLEU score of 62.55. This achievement is particularly noteworthy considering the limited resources available for Vietnamese Sign Language. Moreover, experiments conducted with varying data sizes further solidify the effectiveness of this method within a defined domain. Notably, the BLEU score surpasses expectations for typical translation problems, highlighting the effectiveness of both the probabilistic model and the intuitive linguistic model employed. This study demonstrates the potential of rule-based machine translation for Vietnamese Sign Language, particularly in situations where resources are limited. The encouraging results pave the way for further research and development in this area, ultimately aiming to improve communication and accessibility for the Vietnamese deaf community.
},
 year = {2023}
}

Copy | Download

TY  - JOUR
T1  - Rule-Based Machine Translation for the Automatic Translation of Vietnamese Sign Language
AU  - Thi-Bich-Diep Nguyen
AU  - Thi-Tam Nguyen
Y1  - 2023/12/18
PY  - 2023
N1  - https://doi.org/10.11648/j.ijll.20231106.12
DO  - 10.11648/j.ijll.20231106.12
T2  - International Journal of Language and Linguistics
JF  - International Journal of Language and Linguistics
JO  - International Journal of Language and Linguistics
SP  - 191
EP  - 198
PB  - Science Publishing Group
SN  - 2330-0221
UR  - https://doi.org/10.11648/j.ijll.20231106.12
AB  - Sign language is acknowledged as a unique language in the field of machine translation, possessing distinct grammatical characteristics compared to written or spoken Vietnamese. These include simplifications, altered word order, and emphasis on stress. This article explores a rule-based machine translation approach specifically designed to translate Vietnamese utterances into grammatically accurate Vietnamese Sign Language sentences. While considered a conventional technique, this approach demonstrates remarkable success in this specific scenario. Evaluation results reveal that the proposed method outperforms several contemporary machine translation models for this particular challenge, achieving a BLEU score of 62.55. This achievement is particularly noteworthy considering the limited resources available for Vietnamese Sign Language. Moreover, experiments conducted with varying data sizes further solidify the effectiveness of this method within a defined domain. Notably, the BLEU score surpasses expectations for typical translation problems, highlighting the effectiveness of both the probabilistic model and the intuitive linguistic model employed. This study demonstrates the potential of rule-based machine translation for Vietnamese Sign Language, particularly in situations where resources are limited. The encouraging results pave the way for further research and development in this area, ultimately aiming to improve communication and accessibility for the Vietnamese deaf community.

VL  - 11
IS  - 6
ER  -

Copy | Download