Abstract:
Recent advancements in artificial intelligence (AI), particularly the generative language models driven by deep learning and empowering chatbots such as ChatGPT and GPT-4, have unlocked exciting opportunities for translation technology. These advances could offer immense value to specialized fields, including financial translation, which plays a critical role in ensuring transparency in Hong Kong’s financial market and enhancing its position as an international financial hub.
In light of these developments, this talk aims to explore how cutting-edge AI technologies can contribute to innovation in technology for financial translation. It will begin with an overview of financial translation in Hong Kong and recent breakthroughs in AI, with a focus on the design and use of deep artificial neural networks. This will be followed by a demonstration of custom-built AI-driven translation applications that leverage these networks, illustrating how such tools can facilitate a range of translation-related tasks in the context of financial translation.
This talk will offer insights into how financial translators can capitalize on state-of-the-art language applications in the era of generative AI. These tools could complement widely-adopted resources such as machine translation for general translation, translation memories, and terminology databases, potentially transforming the ways in which professional translators and AI work together for improved cross-lingual communication in the financial world.
About the Speaker:
Dr. SIU Sai Cheong is an Associate Professor in the School of Translation and Foreign Languages at The Hang Seng University of Hong Kong. He is the Programme Director of the Bachelor of Translation with Business and the Master of Arts in Translation (Computer-aided Translation), and the former Director of Deep Learning Research and Application Centre. His research focuses on translation technology and artificial intelligence for the creative industries. His publicly-funded projects include “Machine Translation of IPO Documents” and “A Hybrid Approach to the Translation of Government Press Releases,” supported by the Innovation and Technology Fund and the Research Grants Council, respectively.
Background Reading (Publications):
Koehn, P. (2020). History. In Neural Machine Translation (pp. 29-40). Cambridge University Press.
Siu, S.C. (2015). Automated pre-editing and post-editing: A hybrid approach to the computerized translation of Initial Public Offering (IPO) prospectuses. In Journal of Translation Technology,1(1), 25–46.
Siu, S.C. (2023). Deep learning and translation technology. In S.W. Chan (Ed.), Routledge Encyclopedia of Translation Technology (2nd ed., pp. 797-817). Routledge.
