B6120 - TECHNOLOGY-ASSISTED INTERPRETING II

Learning outcomes

Students know and are able to employ as independent users advanced techniques and software for the real-time transformation of spoken texts

Course contents

The course includes a theoretical introduction to computer-assisted interpreting and practical exercises in using the different forms of ASR (automated speech recognition) as support. The different forms of ASR as support will be presented and put into practice, with reference to support for individual sources of difficulty problem triggers) and live captions or live-generated transcripts. The working directions will be EN>IT, with some guided self-training between each student's third language and English or Italian.

Readings/Bibliography

Recommended readings:

• Chen, Sijia & Jan-Louis Kruger. 2023. The effectiveness of computer-assisted interpreting: A preliminary study based on English-Chinese consecutive interpreting. Translation and Interpreting Studies 18(3). 399–420. https://doi.org/10.1075/tis.21036.che.
• Chen, Sijia & Jan-Louis Kruger. 2024a. Visual processing during computer-assisted consecutive interpreting: Evidence from eye movements. Interpreting. International Journal of Research and Practice in Interpreting 26(2). 231–252. https://doi.org/10.1075/intp.00104.che.
• Chen, Sijia & Jan-Louis Kruger. 2024b. A computer-assisted consecutive interpreting workflow: training and evaluation. The Interpreter and Translator Trainer 18(3). 380–399. https://doi.org/10.1080/1750399x.2024.2373553.
• Defrancq, Bart, Helena Snoeck & Claudio Fantinuoli. 2024. Interpreters’ performances and cognitive load in the context of a CAI tool. In Sharon Deane-Cox, Ursula Böser & Marion Winters (eds.), Translation, interpreting and technological change: innovations in research, practice and training (Bloomsbury Advances in Translation), 38–58. London: Bloomsbury Academic.
• Desmet, Bart, Mieke Vandierendonck & Bart Defrancq. 2018. Simultaneous interpretation of numbers and the impact of technological support. In Claudio Fantinuoli (ed.), Interpreting and technology, 13–27. Berlin: Language Science Press. https://doi.org/10.5281/zenodo.1493291.
• Fantinuoli, Claudio. 2017. Speech recognition in the interpreter workstation. In João Esteves-Ferreira, Juliet Macan, Ruslan Mitkov & Olaf-Michael Stefanov (eds.), Proceedings of the 39th Conference Translating and the Computer, 25–34. London: Editions Tradulex. https://www.asling.org/tc39/wp-content/uploads/TC39-proceedings-final-1Nov-4.20pm.pdf. (7 October, 2024).
• Defrancq, Bart & Claudio Fantinuoli. 2021. Automatic Speech Recognition in the booth: Assessment of system performance, interpreters’ performances and interactions in the context of numbers. Target 33(1). 73–102. https://doi.org/10.1075/target.19166.def.
• Fantinuoli, Claudio & Maddalena Montecchio. 2023. Defining maximum acceptable latency of AI-enhanced CAI tools. In Óscar Ferreiro Vázquez, Ana Correia & Sílvia Araújo (eds.), Technological innovation put to the service of language learning, translation and interpreting: insights from academic and professional contexts (Lengua, Literatura, Traducción), vol. 2, 213–225. Berlin: Peter Lang. (15 April, 2022).
• Gieshoff, Anne Catherine, Martin Schuler & Zaniyar Jahany. 2024. The augmented interpreter: An exploratory study of the usability of augmented reality technology in interpreting. Interpreting. https://doi.org/10.1075/intp.00108.gie.
• Li, Tianyun & Agnieszka Chmiel. 2024. Automatic subtitles increase accuracy and decrease cognitive load in simultaneous interpreting. Interpreting. John Benjamins 26(2). 253–281. https://doi.org/10.1075/intp.00111.li.
• Pisani, Elisabetta & Claudio Fantinuoli. 2021. Measuring the impact of automatic speech recognition on number rendition in simultaneous interpreting. In Caiwen Wang & Binghan Zheng (eds.), Empirical Studies of Translation and Interpreting: The Post-Structuralist Approach, 181–197. New York: Routledge. https://doi.org/10.4324/9781003017400.
• Prandi, Bianca. 2018. An exploratory study on CAI tools in Simultaneous Interpreting: theoretical framework and stimulus validation. In Claudio Fantinuoli (ed.), Interpreting and technology (Translation and Multilingual Natural Language Processing 11), 29–59. Berlin: Language Science Press. https://langsci-press.org/catalog/book/209.
• Prandi, Bianca. 2023. Computer-Assisted Simultaneous Interpreting: A Cognitive-Experimental Study on Terminology (Translation and Multilingual Natural Language Processing 22). Berlin: Language Science Press. https://doi.org/10.5281/zenodo.7143056.
• Van Cauwenberghe, Goran. 2020. Étude expérimentale de l’impact d’un soutien visuel automatisé sur la restitution de terminologie spécialisée. Ghent: Universiteit Ghent MA thesis.
• Yuan, Lu & Binhua Wang. 2023. Cognitive processing of the extra visual layer of live captioning in simultaneous interpreting. Triangulation of eye-tracked process and performance data. Ampersand 11. 100131. https://doi.org/10/gsc8x8.

Teaching methods

As this course presupposes the use of electrical equipment and PCs, please complete e-learning modules 1 and 2 of the mandatory training on safety in the workplace before the course starts: https://site.unibo.it/tutela-promozione-salute-sicurezza/it/corsi-di-formazione/formazione-obbligatoria-su-sicurezza-e-salute-per-svolgimento-di-tirocinio-tesi-laboratorio.

Assessment methods

The assessment will consist of a practical test carried out during the examination sessions.

Students with specific learning difficulties (SpLD) or with disabilities that can affect their ability to attend courses are invited to contact the University service for students with disabilities and SLD at the earliest opportunity -- ideally before the start of the course: https://site.unibo.it/studenti-con-disabilita-e-dsa/en/for-students. The University service will suggest possible adjustments to the course work and/or exam, which must then be submitted to the course leader so they can assess their feasibility, in line with the learning objectives of the course. Please note that adjustments to the exam must be requested at least two weeks in advance.

Teaching tools

All students will be provided with the software applications required throughout the course, or will be able to download them for free.

Support materials (texts, slides, instructions etc.) are made available through the Virtuale e-learning platform.

Office hours

See the website of Bianca Prandi

See the website of Ira Torresi