Audiovisual translation, translators, and technology: From automation pipe dream to human–machine convergence
DOI:
https://doi.org/10.52034/lans-tts.v22i.776Keywords:
digitalization, Machine Translation, MT, Audiovisual Translation, AVT, translation technologyAbstract
Audiovisual translation (AVT), broadly understood as a synonym for media content localization, and not only as a particular practice of linguistic transfer, is undergoing a revolution that was unthinkable only a few years ago – even in those territories where viewers are less accustomed to localized content. Digitalization and technological changes, which have had such an impact on the way audiovisual texts – whether original, localized, or adapted – are produced, distributed, edited, consumed, and shared have also had a substantial impact on the AVT profession. This article explores the ways in which technology has been evolving as an aid to translators: from being merely a clerical aid for transcribing digital texts to automating tasks and integrating machine translation into human translation processes. This it does by providing a range of tools to assist translators in their work processes, progressively migrating both tools and processes to cloud-based environments. The focus is then on AVT, and more particularly on dubbing, where digitalization has shaped the consumer market and posed several challenges to language technology developments and AVT professional practices. Academia has also paid attention to such developments and has increasingly dealt with a number of matters affecting both practice and training to cater to the needs of current media markets. A final word is devoted to proposing a literacy-based framework for the training of translators that embraces technology so as to incorporate automation as an additional aid and which redefines the audiovisual translator’s workstation.
References
Automatic Language Processing Advisory Committee (ALPAC). (1966). Language and machines: Computers in translation and linguistics.
Álvarez Vidal, S., Oliver, A., & Badia, T. (2020). Post-editing for professional translators?: Cheer or fear? Tradumàtica, 18, 49–69. https://doi.org/10.5565/REV/TRADUMATICA.275
Alonso, E., & Vieira, L. N. (2017). The Translator’s Amanuensis 2020. The Journal of Specialised Translation, 28, 345–361.
ATAA. (2021). Les mirages de la post-édition. https://beta.ataa.fr/blog/article/les-mirages-de-la-post-edition
Audiovisual Translators Europe (AVTE). (2021). Machine translation manifesto. https://avteurope.eu/avte-machine-translation-manifesto/
Austermühl, F. (2001). Electronic tools for translators. St. Jerome.
Bar-Hillel, Y. (1964). Language and information: Selected essays on their theory and application. Addison-Wesley.
Bloomberg Media. (2022). Bloomberg Media partners with speech AI dubbing start-up Papercup to localize its award-winning news for Spanish-speaking countries. https://www.bloombergmedia.com/press/bloomberg-media-partners-with-speech-ai-dubbing-start-up-papercup-to-localize-its-award-winning-news-for-spanish-speaking-countries/
Bolaños-García-Escribano, A., & Díaz-Cintas, J. (2020). The cloud turn in audiovisual translation. In ?. Bogucki & M. Deckert (Eds.), The Palgrave handbook of audiovisual translation and media accessibility (pp. 519–544). Palgrave Macmillan. https://doi.org/10.1007/978-3-030-42105-2_26
Bowker, L., & Buitrago, J. (2019). Machine translation and global research: Towards improved machine translation literacy in the scholarly community. Emerald Group. https://doi.org/10.1108/9781787567214
Bylykbashi, K. (2019). The big business of dubbing. Television Business International. https://tbivision.com/2019/04/04/the-big-business-of-dubbing/
Bywood, L. (2020). Technology and audiovisual translation. In ?. Bogucki & M. Deckert (Eds.), The Palgrave handbook of audiovisual translation and media accessibility (pp. 503–517). Palgrave Macmillan. https://doi.org/10.1007/978-3-030-42105-2_25
Cadwell, P., O’Brien, S., & Teixeira, C. S. C. (2017). Resistance and accommodation: Factors for the (non-) adoption of machine translation among professional translators. Perspectives, 26(3), 301–321. https://doi.org/10.1080/0907676X.2017.1337210
Castilho, S., Moorkens, J., Gaspari, F., Calixto, I., Tinsley, J., & Way, A. (2017). Is neural machine translation the new state of the art? The Prague Bulletin of Mathematical Linguistics, 108(1), 109–120. https://doi.org/10.1515/pralin-2017-0013
Chaume, F. (2012). Audiovisual translation: Dubbing. St. Jerome.
Chaume, F., & de los Reyes Lozano, J. (2021). El doblaje en la nube: La última revolución en la localización de contenidos audiovisuales. In B. Reverter Oliver, J. J. Martínez Sierra, D. González Pastor, & J. F. Carrero Martín (Eds.), Modalidades de traducción audiovisual: Completando el espectro (pp. 1–15). Editorial Comares.
Cid-Leal, P., Espín-García, M. C., & Presas, M. (2019). Machine translation and post-editing: Profiles and competences in translator training programmes. MonTI: Monografías de Traducción e Interpretación, 2019(11), 187–214. https://doi.org/10.6035/MONTI.2019.11.7
Deck, A. (2021). The global streaming boom is creating a severe translator shortage. Rest of World. https://restofworld.org/2021/lost-in-translation-the-global-streaming-boom-is-creating-a-translator-shortage/
Diaz-Cintas, J., & Massidda, S. (2019). Technological advances in audiovisual translation. In M. O’Hagan (Ed.), The Routledge handbook of translation and technology (pp. 255-270). Routledge. https://doi.org/10.4324/9781315311258
Díaz-Cintas, J., & Remael, A. (2007). Audiovisual translation: Subtitling. St. Jerome.
Doherty, S. (2016). The impact of translation technologies on the process and product of translation. International Journal of Communication, 10, 947–969.
Elmborg, J. (2006). Critical information literacy: Implications for instructional practice. Journal of Academic Librarianship, 32(2), 192–199. https://doi.org/10.1016/j.acalib.2005.12.004
Federico, M., Enyedi, R., Barra-Chicote, R., Giri, R., Isik, U., Krishnaswamy, A., & Sawaf, H. (2020). From speech-to-speech translation to automatic dubbing. Proceedings of the 17th International Conference on Spoken Language Translation, 257–264. https://doi.org/10.18653/V1/2020.IWSLT-1.31
Fenner, A. (2000). The choices facing translators. Institute of Translation and Interpreting Bulletin, April 2000, 9.
Fisher, C. (1968). Confusiones entre consonantes percibidas visualmente. Revista de investigación del habla y la audición, 11(4), 796–804.
Flawless. (n.d.). https://www.flawlessai.com/
Forte, M., Jacobson, T., Mackey, T., O’Keeffe, E., Stone, K., & Sales, D. (trad.) (2020). Metas y Objetivos de Aprendizaje de la Meta-alfabetización. Metaliteracy.org. https://metaliteracy.org/learning-objectives/goals-and-learning-objectives-translated/metas-y-objetivos-de-aprendizaje-de-la-meta-alfabetizacion/
Fulford, H. (2002). Freelance translators and machine translation: An investigation of perceptions, uptake, experience and training needs. Proceedings of the 6th EAMT Workshop: Teaching Machine Translation, 117–122.
Fulford, H., & Granell-Zafra, J. (2004). The freelance translator’s workstation: An empirical investigation. Proceedings of the 9th EAMT Workshop: Broadening horizons of machine translation and its applications, 53–61.
Fulford, H., & Granell-Zafra, J. (2005). Translation and technology: A study of UK freelance translators. JoSTrans, The Journal of Specialised Translation, 4, 2–17.
Gaspari, F., & Hutchins, J. (2007). Online and free! Ten years of online machine translation: Origins, developments, current use and future prospects. Proceedings of Machine Translation Summit XI: Papers.
Gaspari, F. (2004). Online MT services and real users’ needs: An empirical usability evaluation. In R. E. Frederking & K. B. Taylor (Eds.), Machine translation: From real users to research (pp. 74–85). Springer. https://doi.org/10.1007/978-3-540-30194-3_9
Goad, T. W. (2002). Information literacy and workplace performance. Greenwood.
González-Iglesias, J. D. (2012). Desarrollo de una herramienta de análisis de los parámetros técnicos de los subtítulos y estudio diacrónico de series estadounidenses de televisión en DVD [Doctoral dissertation]. Universidad de Salamanca.
González Pastor, D. (2021). Introducing machine translation in the translation classroom: A survey on students’ attitudes and perceptions. Tradumàtica: Tecnologies de la traducció, 19, 47–65. https://doi.org/10.5565/rev/tradumatica.273
González Pastor, D., & Rico, C. (2021). POSEDITrad: La traducción automática y la posedición para la formación de traductores e intérpretes. Revista Digital de Investigación en Docencia Universitaria, 15(1). https://doi.org/10.19083/10.19083/ridu.2021.1213
Granell, X. (2015). Multilingual information management: Information, technology and translators. Elsevier/Chandos. https://doi.org/10.1016/C2014-0-01998-3
Granell, X., & Martí Ferriol, J. L. (2016). Tecnologías de la Información y la comunicación para el doblaje. In B. Cerezo Mercha?n, F. Chaume, X. Granell, J. L. Martí Ferriol, J. J. Martínez Sierra, A. Marzà, & G. Torralba Miralles (Eds.), La traduccio?n para el doblaje en Espan?a: Mapa de convenciones (pp. 123–142). Publicacions de la Universitat Jaume I.
Green, S. (2018, March 15). How digital demand is disrupting dubbing. M&E Journal. https://www.mesaonline.org/2018/03/15/journal-digital-demand-disrupting-dubbing/
Guerberof Arenas, A. (2013). What do professional translators think about post-editing? The Journal of Specialised Translation, 19, 75–95.
Guerberof Arenas, A., & Moorkens, J. (2019). Machine translation and macrum-editing training as part of a master’s programme. The Journal of Specialised Translation, 31, 217–238.
Hamey, Y. (2015). Metaliteracy: Reinventing information literacy to empower learners. The Australian Library Journal, 64(2), 156–156. https://doi.org/10.1080/00049670.2015.1040358
Hayes, L. (2021). Netflix disrupting dubbing. Journal of Audiovisual Translation, 4(1), 1–26. https://doi.org/10.47476/JAT.V4I1.2021.148
Hutchins, J. W. (1996). Computer-based translation systems and tools. ELRA Newsletter, 1(4).
Hutchins, J. W. (2000). Early years in machine translation. John Benjamins. https://doi.org/10.1075/sihols.97
Hutchins, J. W. (1998). Translation technology and the translator. Machine Translation Review, 7, 7–14.
Hutchins, J. W. (2001a). Machine translation and human translation: In competition or in complementation? International Journal of Translation, 13(1–2), 5–20.
Hutchins, J. W. (2001b). Machine translation over fifty years. Histoire Epistémologie Langage, 23(1), 7–31. https://doi.org/10.3406/hel.2001.2815
Hutchins, J. W., & Somers, H. L. (1992). An introduction to machine translation. Academic Press.
International Association of Professional Translators and Interpreters. (2021). ATRAE states its view on post-diting. https://www.iapti.org/iaptiarticle/atrae-state-its-view-on-post-editing/
Igareda, P., & Matamala, A. (2011). Developing a learning platform for AVT: Challenges and solutions. JoSTrans, The Journal of Specialised Translation, 16, 145–162. https://doi.org/10.17533/udea.ikala.8654
International Organization for Standardization. (2017). ISO 18587:2017 - Translation services — Post-editing of machine translation output — Requirements. https://www.iso.org/standard/62970.html
Jiménez-Crespo, M. A. (2020). The “technological turn” in translation studies. Translation Spaces, 9(2), 314–341. https://doi.org/10.1075/TS.19012.JIM
Kanavos, P., & Kartsaklis, D. (2010). Integrating machine translation with translation memory: A practical approach. Proceedings of the Second Joint EM+/CNGL Workshop: Bringing MT to the User: Research on Integrating MT in the Translation Industry, 11–20.
Kay, M. (1980). The proper place of men and machines in language translation. Research report CSL-80-11.
Kay, M. (1997). The proper place of men and machines in language translation. Machine Translation, 12(1), 3–23. https://doi.org/10.1023/A:1007911416676
Kenny, D. (2022). Machine translation for everyone: Empowering users in the age of artificial intelligence. Language Science Press. https://doi.org/10.5281/zenodo.6653406
Koehn, P. (2020). Neural machine translation. Cambridge University Press https://doi.org/10.1017/9781108608480
Lagoudaki, E. (2008). The value of machine translation for the professional translator. Proceedings of the 8th Conference of the Association for Machine Translation in the Americas: Student Research Workshop, 262–269.
Lehmann, W. P., & Stachowitz, R. (1971). Feasibility study on fully automatic high quality translation (pp. 1–50). University of Texas.
Lloyd, A. (2010). Information literacy landscapes: Information literacy in education, workplace and everyday contexts. Elsevier. https://doi.org/10.1533/9781780630298
Locke, N. A. (2005). In-house or freelance?: A translator’s view. MultiLingual Computing & Technology, 16(1), 19–21.
Lommel, A. R. (2018). Augmented translation: A new approach to combining human and machine capabilities. Proceedings of the 13th Conference of the Association for Machine Translation in the Americas (Volume 2: User Track), 5–12.
Mackey, T. P., & Jacobson, T. E. (2011). Reframing information literacy as a metaliteracy. College and Research Libraries, 72(1), 62–78. https://doi.org/10.5860/crl-76r1
Mackey, T. P., & Jacobson, T. (2014). Metaliteracy: Reinventing information literacy to empower learners. Facet.
Marcum, J. W. (2002). Rethinking information literacy. The Library Quarterly, 72(1). https://doi.org/10.1086/603335
Marking, M. (2022). Netflix COO reveals scale of dubbing and subtitling operations. Slator. https://slator.com/netflix-coo-reveals-scale-of-dubbing-subtitling-operations/
Martí Ferriol, J. L. (2009). Herramientas informáticas disponibles para la automatización de la traducción audiovisual (“revoicing”). Meta: Journal des Traducteurs / Translators’ Journal, 54(3), 622–630. https://doi.org/10.7202/038319ar
Martí Ferriol, J. L. (2012). Nueva aproximación al cálculo de velocidades de lectura de subtítulos. Trans: Revista de Traductogía, 16, 39–48. https://doi.org/10.24310/TRANS.2012.v0i16.3210
Matamala, A. (2005). La estacíon de trabajo del traductor audiovisual: Herramientas y recursos. Cadernos de Tradução, 2(16), 251–268.
Mejías-Climent, L., & de los Reyes Lozano, J. (2021). Traducción automática y posedición en el aula de doblaje: Resultados de una experiencia docente. Hikma, 20(2), 203–227. https://doi.org/10.21071/hikma.v20i2.13383
Melby, A. K. (1982). Multi-level translation aids in a distributed system. In J. Horecký (Ed.), COLING '82: Proceedings of the 9th conference on computational linguistics – Volume 1 (pp. 215–220). North Holland. https://doi.org/10.3115/991813.991847
Melby, A. K. (1992). The translator workstation. In J. Newton (Ed.), Computers in Translation: A practical appraisal (pp. 147–165). Routledge.
Melby, A. K. (1998). Eight types of translation technology. American Translators Association, 4–9.
Melby, A. K. (2007). MT+TM+QA: The future is ours. Tradumàtica: Traducció i Tecnologies de La Informació i La Comunicació, 4, 1–7.
Melby, A. K. (2012). Terminology in the age of multilingual corpora. Journal of Specialised Translation, 18, 7–29.
Melby, A. K. (2019). Future of machine translation: Musings on Weaver’s memo. In M. O’Hagan (Ed.), The Routledge handbook of translation and technology (pp. 419–436). Routledge. https://doi.org/10.4324/9781315311258-25
Media & Entertainment Services Alliance. (2022). The talent crunch: Does it exist and can it be addressed? Content Workflow Management Forum 2022. https://www.mesaonline.org/conferences/content-workflow-management-forum-2022/
Moorkens, J. (2018). What to expect from neural machine translation: A practical in-class translation evaluation exercise. 12(4), 375–387. https://doi.org/10.1080/1750399X.2018.1501639
Moorkens, J., & O’Brien, S. (2015). Post-editing evaluations: Trade-offs between novice and professional participants. Proceedings of the 18th Annual Conference of the European Association for Machine Translation, 75–81.
O’Brien, S., & Salis, B. (2002). Teaching post-editing: A proposal for course content. Proceedings of the 6th EAMT workshop: Teaching machine translation, 99–106.
O’Brien, S., & Conlan, O. (2018). Moving towards personalising translation technology. In H. V. Dam, M. N. Brøgger, & K. K. Zethsen (Eds.), Moving boundaries in translation studies (pp. 81–97). Routledge. https://doi.org/10.4324/9781315121871-6
O’Hagan, M. (2013). The impact of new technologies on translation studies: A technological turn? In C. Millán & F. Bartrina (Eds.), The Routledge handbook of translation studies (pp. 521–536). Routledge. https://doi.org/10.4324/9780203102893.ch37
O’Hagan, M. (Ed.). (2019). The Routledge handbook of translation and technology. Routledge. https://doi.org/10.4324/9781315311258
Pérez-Ortiz, J., Forcada, M., & Sánchez-Martínez, F. (2022). How neural machine translation works. In D. Kenny (Ed.), Machine translation for everyone: Empowering users in the age of artificial intelligence (pp. 141–164). Language Science Press. https://doi.org/10.5281/zenodo.6760020
Pinto, M., García-Marco, J., Granell, X., & Sales, D. (2014). Assessing information competences of translation and interpreting trainees: A study of proficiency at Spanish universities using the InfoliTrans test. Aslib Journal of Information Management, 66(1), 77–95. https://doi.org/10.1108/AJIM-05-2013-0047
Pinto, M., & Sales, D. (2007). A research case study for user-centred information literacy instruction: Information behaviour of translation trainees. Journal of Information Science, 33(5), 531–550. https://doi.org/10.1177/0165551506076404
Rico Pérez, C. (2017). La formación de traductores en traducción automática. Tradumàtica: Tecnologies de la traducció, 15, 75–96. https://doi.org/10.5565/rev/tradumatica.200
Rothwell, A., Moorkens, J., Fernández-Parra, M., Drugan, J., & Austermuehl, F. (2023). Translation tools and technologies. Routledge. https://doi.org/10.4324/9781003160793
Sakamoto, A. (2019). Why do many translators resist post-editing?: A sociological analysis using Bourdieu’s concepts. The Journal of Specialised Translation, 31, 201–216.
Sales, D., & Pinto, M. (2011). The professional translator and information literacy: Perceptions and needs. Journal of Librarianship and Information Science, 43(4), 246–260. https://doi.org/10.1177/0961000611418816
Sales Salvador, D. (2022). Threading metaliteracy into translation and interpreting undergraduates’ information literacy training: A reflective active learning approach. Anales de Documentación, 25, 1–4. https://doi.org/10.6018/ANALESDOC.504691
Sánchez-Mompeán, S. (2021). Netflix likes it dubbed: Taking on the challenge of dubbing into English. Language & Communication, 80, 180–190. https://doi.org/10.1016/J.LANGCOM.2021.07.001
Shields, M. (1999). Slaves to the computer. Institute of Translation and Interpreting Bulletin, October 19, 4–5.
Slocum, J. (1988). Machine translation systems. Cambridge University Press.
Spiteri Miggiani, G. (2021). English-language dubbing: Challenges and quality standards of an emerging localisation trend. The Journal of Specialised Translation, 36a, 2–25.
Spiteri Miggiani, G. (2022). The dubbing metamorphosis: Where do we go from here? EST Newsletter, 60, 10.
Taylor, S. L., Mahler, M., Theobald, B.-J., & Matthews, I. (2012). Dynamic units of visual speech. In J. Lee & P. Kry, Eurographics/ ACM SIGGRAPH Symposium on Computer Animation (pp. 275–284). https://doi.org/10.2312/SCA/SCA12/275-284
The Economist. (2019). Invasion of the voice snatchers. 115–117.
Thies, J., Zollhöfer, M., Stamminger, M., Theobalt, C., & Nießner, M. (2020). Face2Face: Real-time face capture and reenactment of RGB videos. Communications of the ACM, 62(1), 96–104. https://doi.org/10.48550/arxiv.2007.14808
Torralba Miralles, G., Tamayo Masero, A., Mejías Climent, L., Martínez Sierra, J. J., Martí Ferriol, J. L., Granell, X., de los Reyes Lozano, J., de Higes Andino, I., Chaume, F., & Cerezo Merchán, B. (2019). La traduccio?n para la subtitulacio?n en Espan?a: mapa de convenciones. Publicacions de la Universitat Jaume I.
Tuominen, K., Savolainen, R., & Talja, S. (2005). Information literacy as a sociotechnical practice. The Library Quarterly, 75(3), 329–345. https://doi.org/10.1086/497311
UNESCO. (n.d.). Media and Information Literacy. https://iite.unesco.org/mil/
Venkatesan, H. (2018). Teaching translation in the age of neural machine translation. APLX 2017 at Taipei Tech - Transformation and Development: Language, Culture, Pedagogy and Translation, 39–54.
Vieira, L. N. (2018). Automation anxiety and translators. Transl Stud, 13(1), 1–21. https://doi.org/10.1080/14781700.2018.1543613
Vieira, L., Alonso, E., & Bywood, L. (2019). Introduction: Post-editing in practice–process, product and networks. The Journal of Specialised Translation, 31, 2–13.
Weaver, W. (1955). Translation. In W. N. Locke & A. D. Booth (Eds.), Machine translation of languages (pp. 15–23). The Technology Press of MIT.
Yang, J., & Lange, E. D. (1998). SYSTRAN on AltaVista a user study on real-time machine translation on the internet. In D. Farwell, L. Gerber, & E. Hovy (Eds.), Machine translation and the information soup: Third conference of the association for machine translation in the Americas (pp. 275–285). Springer. https://doi.org/10.1007/3-540-49478-2_25
Yang, Y., Shillingford, B., Assael, Y., Wang, M., Liu, W., Chen, Y., Zhang, Y., Sezener, E., Cobo, L. C., Denil, M., Aytar, Y., & de Freitas, N. (2020). Large-scale multilingual audio visual dubbing. https://arxiv.org/pdf/2011.03530.pdf
Zaretskaya, A., Pastor, G. C., & Seghiri, M. (2015). Integration of machine translation in CAT tools: State of the art, evaluation and user attitudes. Skase Journal of Translation and Interpretation, 8(1), 76–89.
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 Ximo Granell, Frederic Chaume
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under the CC BY-NC 4.0 Deed that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal. The material cannot be used for commercial purposes.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
