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Advancing Corpus-Based Interpreting Studies: Innovations, Applications, Theoretical Insights and AI Integration
(ACIS 2025)

Symposium Details

Join Us This June!


ACIS 2025, the symposium on corpus-based interpreting studies, will take place on 9–10 June 2025 at Hong Kong Baptist University and online via Zoom. Submit your abstracts by 12 May 2025 to present your innovative ideas on interpreting studies and AI integration.

Abstract Submissions

We invite submissions addressing a wide range of topics related to corpus-based interpreting studies. Discussions on the transformative impact of AI on corpus-based interpreting studies are also highly welcomed.

Publication Opportunities

Selected contributions will have the chance to be included in a post-symposium special issue or edited volume, offering a platform to reach a wider audience and showcase your research.

Hybrid Mode

This symposium features a hybrid event format. Attend in-person at Hong Kong Baptist University or join virtually via Zoom to engage with discussions on corpus-based interpreting studies.

ABOUT THE SYMPOSIUM

AIMS

This event aims to bring together researchers, practitioners, and scholars to explore cutting-edge developments, promote collaboration, and discuss future directions for corpus-based interpreting studies. Key themes include AI-enhanced interpreting systems, human-AI collaboration, and the development of automatic speech recognition (ASR) technologies. By highlighting the transformative implications and innovative ideas on interpreting studies and AI integration, this symposium seeks to advance corpus-based interpreting studies by exploring innovative methodologies, leveraging cutting-edge technologies, and enhancing human-AI Collaboration.

THEMES

  • Methodologies and technologies for building and re-engineering interpreting corpora

  • Data mining techniques and innovative strategies for interpreting research

  • Corpora and the development of computer-assisted tools for interpreting

  • Theoretical advancements in corpus-based interpreting studies

  • Comparative studies of interpreting and translation corpora

  • Identifying and testing “universals” of interpreting through corpus-based research

  • Integration of interpreting corpora with large language models (LLMs) and AI

  • AI-enhanced systems: Leveraging interpreting corpora for innovation

  • Human-AI collaboration in interpreting: Insights from interpreting corpora

  • Automatic speech recognition (ASR) and interpreting: Corpus based development and applications

  • Ethical challenges in compiling and using interpreting corpora

  • Interdisciplinary applications of interpreting corpora in linguistics, communication studies, computational linguistics, cognitive science, and beyond

 

DATES

09-10 June 2025

MODE

On-site at Hong Kong Baptist University & online via Zoom

ORGANISING COMMITTEE

CALL FOR PAPERS

We invite proposals for Individual Presentations (20 minutes with 10 minutes for Q&A) in English.
● Abstracts should be 250–300 words and must clearly outline the research question, methodology, and (if applicable) preliminary findings.
● Submissions must be written in English.
● The submission should include the title of the presentation, the presenter’s name, institution, email address, and a short bio (50 words).
● Submission Deadline: 12 May 2025
● Notification of Acceptance: 15 May 2025


Please submit your abstracts via the bottom:

 

PROGRAMME

Detailed information regarding the symposium, including the symposium programme, will be available after 15 May 2025.

REGISTRATION

Registration is free. More details will be available after 15 May 2025.

IMPORTANT DATES

  • Submission Deadline: 12 May 2025

  • Notification of Acceptance: 15 May 2025

  • Symposium Dates: 09–10 June 2025

CONTACT US

For inquiries, please contact tiis@hkbu.edu.hk with the email subject line “ACIS 2025”. Thank you for your interest in ACIS 2025. We are eagerly anticipating your participation at this exciting symposium! participation at this exciting symposium!

This symposium is supported by the General Research Fund (GRF) of Hong Kong’s Research Grants Council (Project No. 12623122).

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