The 9th Cross-Strait Interpreting Contest cum Roundtable Seminar on Innovations in Interpreter Training in the Era of AI will be held on 20 May 2023 at the University of Macau. The roundtable seminar Innovations in Interpreter Training in the Era of AI will explore the latest innovations in interpreter training in the era of AI. The seminar will feature a number of speakers, including interpreting experts, educators, and technology developers. The seminar will be open to all UM staff and students who are interested in exploring the intersection of AI and interpreting training.

第九屆海峽兩岸口譯大賽暨AI時代口譯培訓改革與創新圓桌研討會將於2023年5月20日在澳門大學隆重舉行。研討會將聚焦AI時代口譯人才培養的最新發展。我們將邀請包括口譯專家、口譯教育家和技術開發專家在內的演講嘉賓共同探討。研討會對所有對AI和口譯教育交叉領域感興趣的澳門大學師生開放。

 

Details of the event are as follows:

Event name: Roundtable Seminar on Innovations in Interpreter Training in the Era of AI

Date: 20 May (Sat)

Venue: Faculty of Arts and Humanities E21A-G035

Time: 09:00 – 15:40

Target Audience: All are welcome

Please register for the Roundtable by 19 May 2023 (Fri) via https://umac.au1.qualtrics.com/jfe/form/SV_expZ1nP8SYCtYk6

Live broadcast (Youtube): https://www.youtube.com/live/mHGASGxsVD4?feature=share

Live broadcast (Bilibili):  https://live.bilibili.com/26057806

For further inquiries, please feel free to contact Ms. Lisa Lam via lisalam@um.edu.mo. Thank you!

 

活動詳情如下：

活動名稱：AI時代口譯培訓改革與創新圓桌研討會

日期：2023年5月20日（星期六）

地點：澳門大學人文學院 E21A-G035

時間：09:00 – 15:40

對象：歡迎有興趣人士

請於2023年5月19日或以前到https://umac.au1.qualtrics.com/jfe/form/SV_expZ1nP8SYCtYk6報名。

現場直播 (Youtube): https://www.youtube.com/live/mHGASGxsVD4?feature=share

現場直播 (Bilibili):  https://live.bilibili.com/26057806

如有任何問題，歡迎透過電郵lisalam@um.edu.mo與林小姐聯繫。 感謝！

 

會議日程表 Roundtable Schedule
時間 Time	活動 Activities
09:00-09:15	開幕致辭 Opening Remarks
09:15-09:35	Jing Chen 陳菁 廈門大學	Towards an Integrated Approach to Interpreter Training
09:35-09:55	Ailing Zhang  張愛玲 上海外國語大學	Relay and retour: The teaching of interpreting into B
09:55-10:15	Jackie Yan Xiu 鄢秀 香港城市大學	Learner difficulties and coping strategies: An investigation of audio description training in an English-Chinese interpreting program in Hong Kong
10:15-10:35	Victoria Lei 李麗青 澳門大學	Interpreting Training: Insights from Neuroscience
10:35-10:50	Break
10:50-11:10	Wei Su 蘇偉 廈門大學	人工智慧視野下的口譯學術論文寫作研究
11:10-11:30	Daniel Hu 胡宗文 臺灣師範大學	TBD
11:30-11:50	Chao Han 韓潮 廈門大學	Exploring automatic assessment of students’ interpreting performance in the age of artificial intelligence
11:50-14:00	Lunch Break
14:00-14:20	Lidi Wang 王立弟 香港中文大學-深圳	The Impact of AI Technology on Interpreter Training
14:20-14:40	Janice Jun Pan 潘珺 香港浸會大學	Artificial intelligence and interpreting: New possibilities for training and professional development
14:40-15:00	Wallace Chen 陳瑞清 美國蒙特雷國際關係學院	Teaching Interpreting Online: Integrating Platforms and Corpus Tools
15:00-15:20	Min Huang 黃敏 武漢大學	An Exploration on an AI-assisted Interpreting Competence Model
15:20-15:40	Yihui Zhao 趙毅慧 西安外國語大學	Interpreting Teaching in Digital Era: Challenges and Solutions

 

 

Jing Chen 陳菁（廈門大學Xiamen University）

Bio: Professor Jing Chen is currently Dean of College of Foreign Languages and Cultures, Xiamen University, China. Her research interests include interpreting quality assessment and interpreting pedagogy. She has published widely in peer-reviewed journals in English and Chinese. She led and completed several large-scale research projects funded by the European Union (i.e., Asia Link – the EU-Asia Interpreting Studies) and the China National Social Sciences Foundation (NSSF). Currently, she is Principle Investigator of a major national-level research project funded by NSSF (2018-2022). She is also serving as Deputy Director in the National Interpreting Committee of Translators Association of China.

Towards an Integrated Approach to Interpreter Training

To perform an interpreter’s function requires a systematic collection of knowledge, skills and personal characteristics working in concert, especially in the era of AI. The training of interpreters is a complex endeavour in which elements related to the process and product of the interpreted communication, and the knowledge and skills required of a professional interpreter should be integrated in pedagogical considerations. In the presentation the speaker proposes that process-oriented and product-oriented pedagogies interact to enable trainees to understand how sub-components of interpreting competence relate to one another in the dynamic interpreting process, and to follow a structured and monitored sequence of learning steps leading to the acquisition of interpreting competence. It is also believed only when professional practice is integrated into course activities can trainers be well informed in their facilitation of learning and students encouraged to work towards professional standards.

 

Ailing Zhang 張愛玲（上海外國語大學Shanghai International Studies University）

Bio: Irene A. Zhang is Professor of Translation and Interpreting Studies and Dean of the Graduate Institute of Interpretation and Translation (GIIT), Shanghai International Studies University (SISU). A conference interpreter by training, Prof. Zhang has been active in interpreter training and research. She is also General Editor of Routledge Studies in East Asian Interpreting and General Editor of the Journal of Translation Studies published by Peter Lang.

Relay and retour: The teaching of interpreting into B

Relay interpreting is frequently required at multilingual and multilateral events, often using English or another regional lingua franca as pivot language(s). With the advent of AI, claims have arisen for direct SI without relying on pivot languages. In this study, I argue that SI with relay cannot be fully replaced by AI and shall remain at the heart of IO conferences and other events involving less commonly taught languages, not least because of the absence of a truly powerful training database for this universal AI framework. But instead, interpreters might be embracing a new paradigm of using AI for assistance with professional work. I explore the implications thereof for educating and training future interpreters and discuss possibilities of this new AI-assisted SI paradigm.

 

Jackie Yan Xiu 鄢秀（香港城市大學City University of Hong Kong）

Bio: Jackie Xiu Yan received her PhD from the University of Texas at Austin, USA. She is now Subject Leader of the MA Translation Program in the Department of Linguistics and Translation at City University of Hong Kong. Her research and teaching interests include interpreter and translator training, audio description, Applied Linguistics and Chinese culture and translation. She has published profusely in these areas. Her books include Research on Translator and Interpreter Training: A collective Volume of Bibliometric Reviews and Empirical Studies on Learners, Cultural Identity and Language Anxiety (edited), The Commentary of the Analects (translation), and Chinese Poems Translated by Arthur Waley (edited). She has also edited a series of history works in Chinese translation,  and served as editor and reviewer for important academic journals. In 2021, she has won a silver medal in the International Exhibition of Inventions of Geneva. She is now President of the Hong Kong Association of University Women (HKAUW).

Learner difficulties and coping strategies: An investigation of  audio description training in an English-Chinese interpreting program in Hong Kong

Audio description (AD) provides an assistive service that helps people who are visually impaired to access audio-visual products (theatre performance, movies and TV programmes). With this service, the life of people who are visually impaired is enriched and they are more likely to feel that they are part of society. Audio description training (ADT) has attracted increasing attention from researchers. Existing studies on ADT are usually based on the trainers’ teaching experience and teacher-centered methodological issues. Only until recently have learner perspectives been explored. The project intends to examine students’ perceived difficulties and coping strategies in AD learning and how AD learning is related to learning interpreting. The participants are translation students enrolled in an interpreting program in Hong Kong. By conducting a three-level grounded theory analysis on the students’ written reflections on their AD learning, this study will take a learner-centered approach in studying ADT, providing empirical support for previous findings on ADT and suggest a possible direction for AD trainers to pursue in addressing learners’ needs in their future training activities.

* This study is partially supported by CityU SIRG Project #7020037

 

Victoria Lei 李麗青（澳門大學Univerisity of Macau）

Bio: Victoria Lei, Associate Professor, member of the Centre for Studies of Translation, Interpreting and Cognition at the University of Macau and Council Member of International Federation of Translators, is a literary historian, translator and conference interpreter. She obtained her PhD in English Literature from the University of Glasgow, UK and is a life member of Clare Hall, University of Cambridge. An active conference interpreter for two decades, her interpreting practice and teaching have led her to focus her research on cognition and interpreting in recent years, and it is her quest to bridge the gap between empirical research, interpreting practice and the classroom. She explores innovative approaches to translation and interpreting process research using technologies including corpus, eye tracking, keylogging and Functional near-infrared spectroscopy. Her current research interest includes brain activation associated with bilingual processing, interaction and coordination of cognitive efforts in simultaneous interpreting, the interaction between professional conference interpreters and their environment.

 

Wei Su蘇偉（廈門大學Xiamen University）

Bio: Professor Wei Su is head of English Department in Xiamen University, China. His research interests include assessment and feedback in interpreter education. In the past five years he published over 10 research articles in SSCI-indexed journals like Interpreting, The Interpreter and Translator Trainer, Language awareness, Language and Education, International Review of Applied Linguistics in Language teaching. His more academic output can be found at https://orcid.org/0000-0003-2204-3418.

口譯教育類論文寫作的核心是口譯文獻梳理整合和研究問題的提出。本研究以博士生課程“口譯教育研究”為個案，對比了ChatGPT這一智慧程式的文獻綜述品質和口譯學習者的文獻綜述品質，從“邏輯性”、“原創性”和“批判性”等多個維度分析了人與機器的學術寫作表現，並為未來學術研究的人機協作路徑和風險規避提出具體建議。

 

Daniel Hu 胡宗文（臺灣師範大學Taiwan Normal University）

Bio: Daniel Hu received a doctoral degree in Classics from the University of California, Santa Barbara, in 2011. He is currently serving as the Chair of the Graduate Institute of Translation and Interpretation at Taiwan Normal University. In addition, he is the Director of the Taiwan Association of Translation and Interpretation. His main interests are in the field of Bible translation and Chinese-English Contrastive Analysis.

 

The aim of this talk is to give an indication of how, when it comes to translation, CHAT GPT represents a vast improvement over Google Translate. By considering a rather difficult piece of text, the talk will show that CHAT GPT is vastly superior to Google Translate at deciphering the meaning of words and sentences. In the second half of the talk, the results of the first half will be extrapolated to the field of interpretation. It will show that, from the point of view of AI, the difference between translation and interpretation is almost immaterial. Computer Assisted Translation represents a threat to translators and interpreters everywhere.

 

Chao Han 韓潮（廈門大學Xiamen University）

Bio: Dr. Chao Han is a professor in the College of Foreign Languages and Cultures at Xiamen University, China. He has developed and delivered instructional modules such as English-Chinese Interpreting, Quantitative Research in Translation and Interpreting (T&I), Testing and Assessment in T&I, and Academic Writing. His research focuses on T&I assessment, T&I reception, and meta-research in T&I. He is especially interested in examining methods, processes, and results of human scoring in T&I assessment, evaluating the efficacy of human-machine collaborative scoring, and exploring automatic assessment of T&I quality. Dr. Han has published 50-plus articles of various genres, including 32 research articles in SSCI/A&HCI-indexed journals such as Interpreting, Target, Language Testing, Language Assessment Quarterly, and Computer Assisted Language Learning. He is co-editor of a recent volume titled Testing and Assessment of Interpreting: Recent Developments from China (Springer Nature), and serves as a member of the Advisory Board of Interpreting (John Benjamins). ORCiD: https://orcid.org/0000-0002-6712-0555

Exploring automatic assessment of students’ interpreting performance in the age of artificial intelligence

Chao Han and Xiaolei Lu

Abstract: Artificial intelligence (AI) is transforming translation and interpreting (T&I) practice, education, and research. One aspect of such transformation pertains to potential means in which T&I quality is assessed in the educational context. Several studies have recently explored and demonstrated how AI and related technologies (e.g., natural language processing) could be harnessed to assess T&I quality (semi-)automatically. In this article, we aimed to extend previous research effort and report on a pilot study in which we utilized Generative Pre-trained Transformer (GPT) models, a series of large language models (LLMs) created by OpenAI such as ChatGPT, to automatically assess 56 English-Chinese interpretations produced by 28 interpreting students. To validate the GPT-based assessments, we correlated the GPT-generated metrics of interpreting quality with those produced by 15 experienced human raters and further calibrated by many-facet Rasch modeling. Pearson’s correlation coefficients were therefore interpreted as an index of concurrent validity. We then compared the correlation matrix with those previously computed based on machine translation evaluation metrics (e.g., BLEU, NIST, METEOR) and BERT-based quality indicators (see Han & Lu 2023; Lu & Han 2022). This pilot study represents one of the initial efforts to leverage the latest technological advancement to automatically assess human interpretation and may motivate further research and discussion on T&I quality assessment in the age of AI.

 

Lidi Wang 王立弟（香港中文大學（深圳）Chinese University of Hong Kong, Shenzhen）

Bio: Prof. Lidi Wang is Head of Division of Translation Studies and Associate Dean of the School of Humanities and Social Science, Chinese University of Hong Kong, Shenzhen. He served as Dean of Graduate School of Translation and Interpretation, Beijing Foreign Studies University and member of the National Steering Committee for MTI Education. He is executive member of Translators Association of China (TAC) and was as an advisor to the China Accreditation Tests for Translators and Interpreters (CATTI) and representative of member institutes of CIUTI. His research interests cover: T&I studies; T&I training and assessment, Chinese cultural and linguistic studies. He has been a long-time translator, interpreter and trainer himself and has published on Chinese linguistics, cognitive studies of translation and interpretation, translator training and assessment. He can be reached at wanglidi@cuhk.edu.cn

The Impact of AI Technology on Interpreter Training

The development of AI is apparently gathering speed and attracting attention of people from different walks of life. While most would see it a welcome sign for technological progress, which brings benefits to the society and its members, the challenges it brings are looming large in the minds of many, not the least teachers and students of languages. There has been growing concerns over issues such as IPR, performance assessment, job security and others. It is useful to know how our students respond to the new technologies now available, which could help us maximize its benefits and to regulate the downside it has on language education.

For that purpose, we are conducting a survey of college students majoring in T&I studies in Mainland China to understand how they are adapting themselves to the technological advancement in their studies and their concern over how this will affect their professional career development as the next generation of interpreters and as language professionals in general.

 

Janice Jun Pan 潘珺（香港浸會大學Hong Kong Baptist University）

Bio: Dr. Jun PAN is Associate Dean (Research) of the Faculty of Arts and an Associate Head and Associate Professor at the Department of Translation, Interpreting and Intercultural Studies at Hong Kong Baptist University. With many years of experience as an interpreter, Dr. PAN has devoted herself to teaching and researching interpreting and translation, covering a wide array of subjects including corpus-based translation/interpreting studies, political discourse and translation/interpreting, digital humanities, learner factors & situated learning in interpreter training, etc. Dr. PAN serves as Co-Editor of Bandung: Journal of the Global South (Brill) and Review Editor of The Interpreter and Translator Trainer (Taylors & Francis). She is also President of the Hong Kong Translation Society, Chair of International Relations of the Hong Kong Association of University Women, and (founding) Executive Committee Member of the University Women Asia (under Graduate Women International).

Artificial intelligence and interpreting: New possibilities for training and professional development

Advancements in artificial intelligence (AI) have sparked concerns in various fields, including interpreting. As a complex human activity of which the very professionalisation relies heavily on technology, interpreting, like many other professions, has faced new challenges. It is therefore crucial to understand what AI is and the new possibilities it can create for training and professional development in our field. This talk, therefore, will explore how innovations in the era of AI are impacting interpreter training, including virtual simulations, task preparation, and performance assessment. Additionally, I will illustrate how the exploration of “big” interpreting data can empower the next generation of interpreters by providing examples of innovative platforms based on this data. Through this discussion, we aim to shed light on the future prospects and challenges of the field.

 

Wallace Chen 陳瑞清（美國蒙特雷國際關係學院Monterey Institute of International Studies）

Bio: Wallace Chen is Professor and Program Head of Chinese-English Translation and Interpretation at the Middlebury Institute of International Studies at Monterey (MIIS). He holds an MA in Chinese-English Translation and Interpretation (MIIS) and a Ph.D. in Corpus-Based Translation Studies (University of Manchester, UK). Professor Chen has been teaching Chinese-English translation and interpretation (T&I) since 1997. He has over 30 years of experience in practicing T&I, providing services to major corporations, government agencies, and international organizations spanning across Asia and North America. Professor Chen lectures in a wide variety of T&I areas, including professional skill development, pedagogy, T&I technology, professional assessment, T&I practice, and corpus-based T&I studies.

Teaching Interpreting Online: Integrating Platforms and Corpus Tools

This paper presents an initial attempt to teach interpreting online, which is now widely adopted by interpreting programs around the world due to the COVID-19 pandemic outbreak. Various online teaching platforms and corpus tools will be covered in this paper, including Google Drive, Moodle, Zoom, GoReact, ZipDX, InterpretBank, Sketch Engine, WebCorp, and OneClick Terms. Online teaching of interpreting involves a series of modules: pre-class preparation, in-class practice and discussion, post-class self-guided practice by the students, online peer critique, online course platform design, assessment of interpreting homework, exam proctoring and grading, and corpus-assisted knowledge management. These modules are highly customizable and can be used to teach the three major modes of interpreting: Sight Translation (ST), Consecutive Interpreting (CI), and Simultaneous Interpreting (SI). Methods and steps to teach these modes of interpreting in the online environment are described, with online student counseling with the instructor as a way to maximize the benefits of teaching interpreting online.

Keywords: online teaching, corpus, assessment of interpreting, sight translation, consecutive interpreting, simultaneous interpreting

 

Min Huang 黃敏（武漢大學Wuhan University）

Bio: Dr. Min Huang is an associate professor and vice dean at the Department of Translation and Interpreting, Wuhan University. He mentors MTI students and has 20 years of experience as an interpreter trainer, an interpreting researcher as well as a part-time interpreter and translator. He is an expert member of the Translators Association of China (TAC) and Committee Member of the Interpreters Committee of TAC, Secretary-general of Translators Association of Hubei (TAHB) and Chairman of the Interpreters’ Committee of TAHB, Vice Director of the Interpreting Education and Assessment Union (IEAU), and Executive Director of the International Association of Translation Interpreting and Cognition (IATIC). He is author of more than 20 interpreting textbooks. His current research interest focuses on interpreting training, interpreting quality assessment and interpreting accreditation testing.

An Exploration on an AI-assisted Interpreting Competence Model

The great development of artificial intelligence (AI) technologies, such as speech recognition, sound-text conversion, machine translation, and speech synthesis, has brought many conveniences to interpreting practice, which has thus changed the traditional human interpreting modes. Hence, the components and their weights of the interpreting competence of human interpreters have gained new features. Therefore, it is necessary to make corresponding adjustments in the content of interpreting training, and interpreting training institutions should explore accordingly new thoughts on curriculum design, training focuses, and textbook writing. This article will modify the existing interpreting competence models, construct an AI-assisted interpreting competence model, and further put forward proposals on a series of issues related to interpreting training.

Key words: artificial intelligence; interpreting competence; interpreting training

 

Yihui Zhao趙毅慧（西安外國語大學Xi’an International Studies University）

Bio: Yihui Zhao, Associate Professor, Deputy Dean of School of Translation Studies of Xi’an International Studies University. She won the China-Canada Exchange Program Scholarship and visited University of Ottawa as senior scholar in 2014. With years of experience in interpreting teaching and practice, she has got various interpreting experience for over 500 international conferences and was employed by the Chief Interpreter of the Shaanxi Provinvial Translators and Interpreters Talent Bank. In 2011, she won the second prize of Shaanxi Provincial Education Award. In recent years, she has published several influential papers in the fields of interpreting technology and interpreting education on well-reputed journals like Foreign Language Teaching, Shanghai Translation, Foreign Language and Foreign Language Teaching, Foreign Language Research, etc. She is currently leading 2 provincial level research programs.

Interpreting Teaching in Digital Era: Challenges and Solutions

Abstract: Computer assisted interpreting training tools (CAIT), derived in the 1990s from computer assisted language learning tools (CALL), are now routinely used in several educational institutions (Kajzer-Wietrzny and Tymczyńska 2014). The next step forward was moving from the physical classroom to virtual environments and experimenting with on-line teaching and learning (Ko 2008; Ko and Chen 2011; Braun and Slater 2014; Motta 2016). The ‘technological turn’ in interpreting (Fantinuoli 2018) has been discussed a lot in recent years particularly heated since the burst-out of COVID-19. This indicates that technology has entered or is entering the realm of interpreting education and practice. This presentation attempts to discuss the positive and negative impact of technology application in interpreting teaching and practice in digital era and to provide some suggestions in terms of computer assisted interpreting teaching.