Ús de la tecnologia en la traducció i la interpretació jurídiques: potencial, disponibilitat i aplicacions dels recursos

Jeffrey Killman, Christopher D. Mellinger

Resum


En aquesta introducció es presenta un resum del número especial que la Revista de Llengua i Dret, Journal of Language and Law dedica a la traducció i la interpretació (TI) jurídiques en el món de les tecnologies. Tot i que les tecnologies de la traducció són àmpliament accessibles i acceptades en molts dominis especialitzats, el seu ús en contextos jurídics ha estat històricament limitat pels recursos financers, institucionals i textuals. La manca de disponibilitat dificulta el desenvolupament d’aplicacions tecnològiques de qualitat que poden ajudar qui treballa professionalment en la TI en contextos jurídics. Les contribucions d’aquest número especial tracten la disponibilitat i l’ús dels recursos des de diferents perspectives. Diversos articles investiguen el desenvolupament de sistemes de traducció automàtica neuronal (TAN) aprofitant els recursos de qualitat de llengües relacionades o amb pocs recursos, mentre que en d’altres s’analitzen els sistemes de traducció automàtica (TA) com a possibles recursos per a la productivitat i la qualitat en traducció. En les col·laboracions també s’estudia l’assignació de recursos institucionals a la formació en traducció i interpretació per treballar en contextos jurídics.

Paraules clau


traducció jurídica; tecnologies de la traducció; traducció automàtica; avaluació de sistemes de TA; assignació de recursos; llengües amb pocs recursos

Cites


Arnejšek, Mateja, & Unk, Alenka. (2020). Multidimensional assessment of the eTranslation output for English–Slovene. In André Martins, Helena Moniz, Sara Fumega, Bruno Martins, Fernando Batista, Luisa Coheur, Carla Parra, Isabel Trancoso, Marco Turchi, Arianna Bisazza, Joss Moorkens, Ana Guerberof, Mary Nurminen, Lena Marg, & Mikel L. Forcada (Eds.), Proceedings of the 22nd annual conference of the European Association for Machine Translation, 383–392. European Association for Machine Translation. https://www.aclweb.org/anthology/2020.eamt-1.41

Biau Gil, José Ramón, & Pym, Anthony. (2006). Technology and translation (a pedagogical overview). In Anthony Pym, Alexander Perekrestenko & Bram Starink (Eds.), Translation technology and its teaching (pp. 5–19). Tarragona: Universitat Rovira i Virgili. http://www.intercultural.urv.cat/media/upload/domain_317/arxius/Technology/translationtechnology.pdf

Biel, Łucja. (2011). “Professional realism in the legal translation classroom: Translation competence and translator competence.” Meta: journal des traducteurs/Meta: Translators’ Journal, 56(1), 162–178. https://doi.org/10.7202/1003515ar

Biel, Łucja. (2017). Enhancing the communicative dimension of legal translation: comparable corpora in the research-informed classroom. The Interpreter and Translator Trainer, 11(4), 316–336. https://doi.org/10.1080/1750399X.2017.1359761

Cadwell, Patrick, Castilho, Sheila, O’Brien, Sharon, & Michell, Linda. (2016). Human factors in machine translation and post-editing among institutional translators. Translation Spaces, 5(2), 222–243. https://doi.org/10.1075/ts.5.2.04cad

Cao, Deborah. (2007). Translating law. Multilingual Matters. https://doi.org/10.21832/9781853599552

Cheng, Le, Sin, King Sui, & Wagner, Anne (Eds.). (2014). The Ashgate handbook of legal translation. Routledge.

Desmet, Luca. (2021). An exploratory study of professional post-edits by English-Dutch DGT Translators. [MA thesis]. Ghent University. [UGent Library repository]

Drechsel, Alexander. (2019). Technology literacy for the interpreter. In David B. Sawyer, Frank Austermühl, & Vanessa Enríquez Raído (Eds.), The Evolving Curriculum in Interpreter and Translator Education: Stakeholder perspectives and voices (pp. 259–268). John Benjamins.

Engberg, Jan. (2020). Comparative law for legal translation: Through multiple perspectives to multidimensional knowledge. International Journal for the Semiotics of Law-Revue internationale de sémiotique juridique, 33(2), 263–282. https://doi.org/10.1007/s11196-020-09706-9

Fantinuoli, Claudio. (2017). Computer-assisted interpreting: challenges and future perspectives. In Gloria Corpas Pastor & Isabel Durán-Muñoz (Eds.), Trends in e-tools and resources for translators and interpreters (pp. 153–174). Brill. https://doi.org/10.1163/9789004351790_009

Fantinuoli, Claudio. (2018). Interpreting and technology: The upcoming technological turn. In Claudio Fantinuoli (Ed.), Interpreting and technology, (pp. 1–12). Language Science Press.

Farzindar, Atefeh, & Lapalme, Guy. (2009). Machine translation of legal information and its evaluation. In Yong Gao & Nathalie Japkowicz (Eds.), Advances in Artificial Intelligence (pp. 64–73). Springer.

Forcada, Mikel L. (2017). Making sense of neural machine translation. Translation Spaces, 6(2), 291–309. https://doi.org/10.1075/ts.6.2.06for

García, Ignacio. (2010). Is machine translation ready yet? Target, 22(1), 7–21. https://doi.org/10.1075/target.22.1.02gar

García, Ignacio. (2011). Translating by post-editing: Is it the way forward? Machine Translation, 25, 217–237. https://doi.org/10.1007/s10590-011-9115-8

Gonzalo Claros, Manuel. (2009). El asistente impasible. Panace@, 10(29), 1–2.

Gotti, Fabrizio, Farzindar, Atefeh, Lapalme, Guy, & Macklovitch, Elliott. (2008). Automatic translation of court judgments. In Proceedings of The Eighth Conference of the Association for Machine Translation in the Americas, 21–25 October 2008, Waikiki, Hawaii, USA (pp. 370–379). https://aclanthology.org/2008.amta-govandcom.11.pdf

Hamidi, Miriam, & Pöchhacker, Franz. (2007). Simultaneous consecutive interpreting: A new technique put to the test. Meta: journal des traducteurs/Meta: Translators' Journal, 52(2), 276–289. https://doi.org/10.7202/016070ar

Heiss, Christine, & Soffritti, Marcello. (2018). DeepL Traduttore e didattica della traduzione dall’italiano in tedesco. inTRAlinea - Special Issue: Translation and Interpreting for Language Learners (TAIL). https://www.intralinea.org/specials/article/2294

Hutchins, John. (2014). Machine translation: History of research and applications. In Chan Sin-wai (Ed.), The Routledge encyclopedia of translation technology (pp. 120–136), Routledge.

Kenny, Dorothy, & Doherty, Stephen. (2014). Statistical machine translation in the translation curriculum: overcoming obstacles and empowering translators. The Interpreter and Translator Trainer, 8(2), 276–294. https://doi.org/10.1080/1750399X.2014.936112

Killman, Jeffrey. (2014). Vocabulary accuracy of statistical machine translation in the legal context. In Sharon O’Brien, Michel Simard & Lucia Specia (Eds.), Third Workshop on Post-Editing Technology and Practice (WPTP-3) (pp. 85–98). AMTA.

Killman, Jeffrey. (2015). Context as Achilles’ heel of translation technologies: Major implications for end-users. Translation and Interpreting Studies, 10(2), 203–222. https://doi.org/10.1075/tis.10.2.03kil

Killman, Jeffrey. (2018). A context-based approach to introducing translation memory in translator training. In Concepción Godev (Ed.), Translation, globalization and translocation (pp. 137–159). Palgrave Macmillan. https://doi.org/10.1007/978-3-319-61818-0_8

Killman, Jeffrey, & Mónica Rodríguez-Castro. (2022). Post-editing vs. Translating in the legal context: Quality and time effects from English to Spanish. Revista de Llengua i Dret, Journal of Language and Law, 78, xx-xx. https://www.doi.org/10.2436/rld.i78.2022.3831

Koehn, Philipp. (2010). Statistical machine translation. Cambridge University Press.

Koehn, Philipp. (2020). Neural machine translation. Cambridge University Press.

Koehn, Philipp, & Knowles, Rebecca. (2017). Six challenges for neural machine translation. In Thang Luong, Alexandra Birch, Graham Neubig & Andrew Finch (Eds.), Proceedings of the First Workshop on Neural Machine Translation (pp. 28–39). Association for Computational Linguistics. https://arxiv.org/pdf/1706.03872.pdf

Lesznyák, Ágnes. (2019). Hungarian translators’ perceptions of neural machine translation in the European Commission. In Proceedings of MT Summit XVIII: Translator, Project and User Tracks, 19–23 August, Dublin (pp. 16–22). https://aclanthology.org/volumes/W19-67/

Macken, Lieve, Prou, Daniel, & Tezcan, Arda. (2020). Quantifying the effect of machine translation in a high-quality human translation production process. Informatics – Special Issue: Feature Paper in Informatics, 7(12), 1–19. https://doi.org/10.3390/informatics7020012

Mileto, Fiorenza. (2019). Post-editing and legal translation. Digital Humanities Journal, 1(1). https://doi.org/10.21814/h2d.237

Monzó-Nebot, Esther, & Mellinger, Christopher D. (2022). Language policies for social justice—Translation, interpreting, and access. Just. Journal of Language Rights & Minorities, Revista de Drets Lingüístics i Minories, 1(1-2), 15–35. https://doi.org/10.7203/Just.1.25367

O’Hagan, Minako. (2013). The impact of new technologies on translation studies: a technological turn?. In The Routledge handbook of translation studies (pp. 521–536). Routledge.

O'Hagan, Minako. (Ed.). (2019). The Routledge handbook of translation and technology. Routledge.

Pontrandolfo, Gianluca. (2019). Discursive constraints in legal translation: a genre-based analytical framework. In Ingrid Simonnaes & Marita Kristiansen (Eds.), Legal Translation. Current Issues and Challenges in Research, Methods and Applications. (pp. 155–183). Frank & Timme.

Prieto Ramos, Fernando. (2011). “Developing legal translation competence: An integrative process-oriented approach.” Comparative Legilinguistics, 5, 7–22. https://doi.org/10.14746/cl.2011.5.01

Prieto Ramos, Fernando. (2014). Parameters for problem-solving in legal translation: Implications for legal lexicography and institutional terminology management. In Le Cheng, King Sui Sin, & Anne Wagner (Eds.), The Ashgate handbook of legal translation (pp. 121–134). Routledge.

Rossi, Caroline, & Chevrot, Jean-Pierre. (2019). Uses and perceptions of machine translation at the European Commission. JoSTrans: The Journal of Specialised Translation, 31, 177–200.

Şahin, Mehmet, & Dungan, Nilgün. (2014). Translation testing and evaluation: A study on methods and needs. Translation & Interpreting, 6(2), 67–90.

Šarčević, Susan. (1997). New approach to legal translation. Kluwer Law International.

Scott, Juliette R. (2019). Legal translation outsourced. Oxford University Press.

Stefaniak, Karolina. (2020). Evaluating the usefulness of neural machine translation for the Polish translators in the European Commission. In André Martins, Helena Moniz, Sara Fumega, Bruno Martins, Fernando Batista, Luisa Coheur, Carla Parra, Isabel Trancoso, Marco Turchi, Arianna Bisazza, Joss Moorkens, Ana Guerberof, Mary Nurminen, Lena Marg, & Mikel L. Forcada (Eds.), Proceedings of the 22nd Annual Conference of the European Association for Machine Translation, 3–5 November, Lisbon (pp. 263–269). European Association for Machine Translation. https://aclanthology.org/2020.eamt-1.28

Vardaro, Jennifer, Schaeffer, Moritz, & Hansen-Schirra, Silvia. (2019). Translation quality and error recognition in professional neural machine translation post-editing. Informatics – Special Issue: Advances in Computer-Aided Translation Technology, 6(41), 1–29. https://doi.org/10.3390/informatics6030041

Velykodska, Olena. (2018). Legal discourse: Text analysis and translation strategies. Comparative Legilinguistics, 34, 53–64. https://doi.org/10.14746/cl.2018.34.3

Way, Catherine. (2016). The challenges and opportunities of legal translation and translator training in the 21st century. International Journal of Communication, 10, 1009–1029.

Wiesmann, Eva. (2019). Machine translation in the field of law: A study of the translation of Italian legal texts into German. Comparative Legilinguistics, 37, 117–153. https://doi.org/10.14746/cl.2019.37.4




DOI: http://dx.doi.org/10.2436/rld.i78.2022.3896



 

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