ViBidirectionMT - Eval: Machine translation for Vietnamese-Chinese and Vietnamese-Lao language pair

This paper presents the results of the VLSP 2022-2023 Machine Translation Shared Tasks, focusing on Vietnamese-Chinese and Vietnamese-Lao machine translation. The tasks were organized as part of the 9th and 10th annual workshops on Vietnamese Language and Speech Processing (VLSP 2022, VLSP 2023). The objective of the shared task was to build machine translation systems, specifically targeting Vietnamese-Chinese and Vietnamese-Lao translation (corresponding to 4 translation directions). The submissions were evaluated on 1,000 test pairs from both news and general domains, using established metrics such as BLEU and SacreBLEU. In addition to these automated evaluations, the system outputs were also assessed through human judgment by experts in the Chinese and Lao languages. These human assessments played a crucial role in ranking the performance of the machine translation models, ensuring a more comprehensive evaluation.

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Publication Details

Journal
Journal of Computer Science and Cybernetics
Published
2025-09-23
DOI
https://doi.org/10.15625/1813-9663/21055
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
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article

ViBidirectionMT - Eval: Machine translation for Vietnamese-Chinese and Vietnamese-Lao language pair

Nguyễn Minh Quý, Nguyen Van Vinh, Tran Hong Viet
Journal of Computer Science and Cybernetics
Natural Language Processing Techniques
article

ViBidirectionMT - Eval: Machine translation for Vietnamese-Chinese and Vietnamese-Lao language pair

Nguyễn Minh Quý, Nguyen Van Vinh, Tran Hong Viet
article en

Abstract

This paper presents the results of the VLSP 2022-2023 Machine Translation Shared Tasks, focusing on Vietnamese-Chinese and Vietnamese-Lao machine translation. The tasks were organized as part of the 9th and 10th annual workshops on Vietnamese Language and Speech Processing (VLSP 2022, VLSP 2023). The objective of the shared task was to build machine translation systems, specifically targeting Vietnamese-Chinese and Vietnamese-Lao translation (corresponding to 4 translation directions). The submissions were evaluated on 1,000 test pairs from both news and general domains, using established metrics such as BLEU and SacreBLEU. In addition to these automated evaluations, the system outputs were also assessed through human judgment by experts in the Chinese and Lao languages. These human assessments played a crucial role in ranking the performance of the machine translation models, ensuring a more comprehensive evaluation.

Journal of Computer Science and Cybernetics
Hanoi National University of Education (VN), Vietnam National University, Hanoi (VN)
Openalex Percentile: Top 86%
Natural Language Processing Techniques
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ViBidirectionMT - Eval: Machine translation for Vietnamese-Chinese and Vietnamese-Lao language pair — Nguyễn Minh Quý, Nguyen Van Vinh, et al. · Journal of Computer Science and Cybernetics (2025) | TGRS Research Map | TGRS