@inproceedings{li-etal-2022-sg,
title = "{SG} Translate Together - Uplifting {S}ingapore{'}s translation standards with the community through technology",
author = "Li, Lee Siew and
Sim, Adeline and
Kanagarajah, Gowri and
Amirah, Siti and
Xiang, Foo Yong and
Ayathorai, Gayathri and
Rasol, Sarina Mohamed and
Ai Ti, Aw and
Kui, Wu and
Weihua, Zheng and
Yang, Ding and
Kumar Vangani, Tarun and
Johan, Nabilah Binte Md",
editor = "Campbell, Janice and
Larocca, Stephen and
Marciano, Jay and
Savenkov, Konstantin and
Yanishevsky, Alex",
booktitle = "Proceedings of the 15th Biennial Conference of the Association for Machine Translation in the Americas (Volume 2: Users and Providers Track and Government Track)",
month = sep,
year = "2022",
address = "Orlando, USA",
publisher = "Association for Machine Translation in the Americas",
url = "https://aclanthology.org/2022.amta-upg.28",
pages = "405--415",
abstract = "The Singapore{'}s Ministry of Communications and Information (MCI) has officially launched the SG Translate Together (SGTT) web portal on 27 June 2022, with the aim of partnering its citizens to improve translation standards in Singapore. This web portal houses the Singapore Government{'}s first neural machine translation (MT) engine, known as SG Translate, which was jointly developed by MCI and the Institute for Infocomm Research (I2R), Agency for Science, Technology and Research (A*STAR). Adapted using localised translation data, SG Translate is able to generate translations that are attuned to Singapore{'}s context and supports Singapore{'}s four (4) official languages {--} English (Singapore), Chinese (Singapore), Bahasa Melayu (Singapore) and Tamil (Singapore). Upon completion of development, MCI allowed all Government agencies to use SG Translate for their daily operations. This presentation will briefly cover the methodologies adopted and showcase SG Translate{'}s capability to translate content involving local culture, everyday life and government policies and schemes. This presentation will also showcase MCI{'}s sustainable approach for the continual training of the SG Translate MT engine through citizenry participation.",
}
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<abstract>The Singapore’s Ministry of Communications and Information (MCI) has officially launched the SG Translate Together (SGTT) web portal on 27 June 2022, with the aim of partnering its citizens to improve translation standards in Singapore. This web portal houses the Singapore Government’s first neural machine translation (MT) engine, known as SG Translate, which was jointly developed by MCI and the Institute for Infocomm Research (I2R), Agency for Science, Technology and Research (A*STAR). Adapted using localised translation data, SG Translate is able to generate translations that are attuned to Singapore’s context and supports Singapore’s four (4) official languages – English (Singapore), Chinese (Singapore), Bahasa Melayu (Singapore) and Tamil (Singapore). Upon completion of development, MCI allowed all Government agencies to use SG Translate for their daily operations. This presentation will briefly cover the methodologies adopted and showcase SG Translate’s capability to translate content involving local culture, everyday life and government policies and schemes. This presentation will also showcase MCI’s sustainable approach for the continual training of the SG Translate MT engine through citizenry participation.</abstract>
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%0 Conference Proceedings
%T SG Translate Together - Uplifting Singapore’s translation standards with the community through technology
%A Li, Lee Siew
%A Sim, Adeline
%A Kanagarajah, Gowri
%A Amirah, Siti
%A Xiang, Foo Yong
%A Ayathorai, Gayathri
%A Rasol, Sarina Mohamed
%A Ai Ti, Aw
%A Kui, Wu
%A Weihua, Zheng
%A Yang, Ding
%A Kumar Vangani, Tarun
%A Johan, Nabilah Binte Md
%Y Campbell, Janice
%Y Larocca, Stephen
%Y Marciano, Jay
%Y Savenkov, Konstantin
%Y Yanishevsky, Alex
%S Proceedings of the 15th Biennial Conference of the Association for Machine Translation in the Americas (Volume 2: Users and Providers Track and Government Track)
%D 2022
%8 September
%I Association for Machine Translation in the Americas
%C Orlando, USA
%F li-etal-2022-sg
%X The Singapore’s Ministry of Communications and Information (MCI) has officially launched the SG Translate Together (SGTT) web portal on 27 June 2022, with the aim of partnering its citizens to improve translation standards in Singapore. This web portal houses the Singapore Government’s first neural machine translation (MT) engine, known as SG Translate, which was jointly developed by MCI and the Institute for Infocomm Research (I2R), Agency for Science, Technology and Research (A*STAR). Adapted using localised translation data, SG Translate is able to generate translations that are attuned to Singapore’s context and supports Singapore’s four (4) official languages – English (Singapore), Chinese (Singapore), Bahasa Melayu (Singapore) and Tamil (Singapore). Upon completion of development, MCI allowed all Government agencies to use SG Translate for their daily operations. This presentation will briefly cover the methodologies adopted and showcase SG Translate’s capability to translate content involving local culture, everyday life and government policies and schemes. This presentation will also showcase MCI’s sustainable approach for the continual training of the SG Translate MT engine through citizenry participation.
%U https://aclanthology.org/2022.amta-upg.28
%P 405-415
Markdown (Informal)
[SG Translate Together - Uplifting Singapore’s translation standards with the community through technology](https://aclanthology.org/2022.amta-upg.28) (Li et al., AMTA 2022)
ACL
- Lee Siew Li, Adeline Sim, Gowri Kanagarajah, Siti Amirah, Foo Yong Xiang, Gayathri Ayathorai, Sarina Mohamed Rasol, Aw Ai Ti, Wu Kui, Zheng Weihua, Ding Yang, Tarun Kumar Vangani, and Nabilah Binte Md Johan. 2022. SG Translate Together - Uplifting Singapore’s translation standards with the community through technology. In Proceedings of the 15th Biennial Conference of the Association for Machine Translation in the Americas (Volume 2: Users and Providers Track and Government Track), pages 405–415, Orlando, USA. Association for Machine Translation in the Americas.