Traducción Automática y Posedición en TAVestudio piloto de una práctica en alza

Referencias bibliográficas

• Agulló García, B. (2020). El paradigma actual de la subtitulación: cambios en la distribución de contenido, nuevos hábitos de consumo y avances tecnológicos. La linterna del traductor, 20, 53-62.
• Alves, F., Sarto Szpak, K., Gonçalves, J. L., Sekino, K., Aquino, M., Araújo e Castro, R., Koglin, A., de Lima Fonseca, N. B. & Mesa-Lao, B (2016). Investigating cognitive effort in postediting: A relevance-theoretical approach. In S. Hansen-Schirra & S. Grucza (Eds.), Eyetracking and Applied Linguistics (pp. 109-142). Language Science Press. http://10.17169/langsci.b108.296
• AppTek (2021, September 20). This Is How Automatic Speech Recognition & Machine Translation Are Revolutionizing Subtitling. Slator. https://slator.com/automatic-speech-recognition-machine-translation-are-revolutionizing-subtitling/
• Aranberri, N. (2014). Posedición, productividad y calidad. Revista Tradumàtica. Tecnologies de la Traducció, 12, 471-477. https://doi.org/10.5565/rev/tradumatica.62
• Asociación Española de Traductores, Correctores e Intérpretes (ASETRAD) (2021). Posedición. Guía para profesionales. Asetrad.
• ATAA (2022, October 3). Machine-translated subtitling – human translators are up in arms. Association des traducteurs adaptateurs de l’audiovisuel. https://beta.ataa.fr/blog/article/machine-translated-subtitling-human-translators-are-up-in-arms
• Athanasiadi, R. (2021). Technology as a driving force in subtitling. In L. Mejías-Climent & J. F. Carrero Martín (Eds.), New Perspectives in Audiovisual Translation. Towards Future Research Trends (pp. 139-166). Universitat de València.
• ATRAE (2021, October 13). Comunicado sobre la posedición. Asociación de Traducción y Adaptación Audiovisual de España. https://atrae.org/comunicado-sobre-la-posedicion/
• ATRAE (2022, September 27). Comunicado sobre el uso de lenguas puente. Asociación de Traducción y Adaptación Audiovisual de España. https://atrae.org/comunicado-sobre-el-uso-de-lenguas-puente/
• AVTE (2021). Machine translation manifesto. Audiovisual Translators Europe. The European Federation of Audiovisual Translators. https://avteurope.eu/avte-machine-translation-manifesto/
• Bellés-Calvera, L. & Caro Quintana, R. (2021). Audiovisual Translation through NMT and Subtitling in the Netflix Series Cable Girls. Translation and Interpreting Technology Online, 142-148. https://doi.org/10.26615/978-954-452-071-7_015
• Bolaños-García-Escribano, A., Díaz-Cintas, J. & Massidda, S. (2021). Subtitlers on the Cloud: The Use of Professional Web-based Systems in Subtitling Practice and Training. Revista Tradumàtica. Tecnologies de la Traducció, 19, 1-21. https://doi.org/10.5565/rev/tradumatica.276
• Bruno, L., Miloro, A., Sabaté-Carrové, P. E. & Sabaté-Carrové, M. (2021). Preconceptions from pre-professionals about MTPE. In M. Sabaté-Carrové & L. Baudo (Eds.), The translation process series. Multiple perspective from teaching to professional practice. Volume 1 (pp. 41-44). Edicions de la Universitat de Lleida.
• Bundgaard, K. (2017). Translator attitudes towards translator-computer interaction - Findings from a workplace study. Hermes-Journal of Language and Communication in Business, 56, 125-144. https://doi.org/10.7146/hjlcb.v0i56.97228
• Burchardt, A., Lommel, A., Bywood, L., Harris, K. & Popović, M. (2016). Machine translation quality in an audiovisual context. Target 28(2), 206-221.
• Bywood, L. & Georgakopoulou, Y. (2017). Embracing the threat: machine translation as a solution for subtitling. Perspectives Studies in Translatology 25(3), 1-17. http://10.1080/0907676X.2017.1291695
• 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
• Cantos, P. & Sánchez, A. (2011). El inglés y el español desde una perspectiva cuantitativa y distributiva: equivalencias y contrastes. Estudios Ingleses de la Universidad Complutense, 19, 15-44.
• Carl, M., Dragsted, B., Elming, J., Hardt, D. & Jakobsen, A. L. (2011). The process of post-editing: a pilot study. In B. Sharp, M. Zock, M. Carl & A. L. Jakobsen (Eds.), Proceedings of the 8th international NLPSC workshop. Special theme: Human-machine interaction in translation (pp. 131-142). Copenhagen Business School.
• Díaz-Cintas, J. & S. Massidda (2020). Technological advances in audiovisual translation. In M. O’Hagan (Ed.), The Routledge Handbook of Translation and Technology (pp. 225-270). Routledge.
• European Language Industry Survey (ELIS) (2023). Trends, expectations and concerns of the European language industry. https://elis-survey.org/wp-content/uploads/2023/03/ELIS-2023-report.pdf
• Eriksen (2019, March 6). Text Expansion and contraction in Translation. Eriksen Translation. https://eriksen.com/language/text-expansion/
• Estopace, E. (2018, January 22). From Indonesia to Nigeria: Inside iflix’s Localization Rollout. Slator. https://slator.com/indonesia-nigeria-inside-iflixs-localization-rollout/
• Fernández Moriano, P. (2019). Herramientas informáticas para traductores audiovisuales. In J. F. Carrero Martín, B. Cerezo Merchán, J. J. Martínez Sierra & G. Zaragoza Ninet (Eds.), La traducción audiovisual: aproximaciones desde la academia y la industria (pp. 73-92). Comares.
• Fernández-Torné, A. & Matamala, A. (2015). Text-to-Speech vs. Human Voiced Audio Descriptions: A Reception Study in Films Dubbed into Catalan. The Journal of Specialised Translation, 24, 61-88.
• Firat, G. (2021). Uberization of translation. Impacts on working conditions. The Journal of Internationalisation and Localization, 8(1), 48-75. https://doi.org/10.1075/jial.20006.fir
• Gaspari, F., Almaghout, F. & Doherty, S. (2015). A survey of machine translation competences: Insights for translation technology educators and practitioners. Perspectives, 23(3), 333-358.
• Georgakopoulou, P. (2006). Subtitling and globalisation. The Journal of Specialised Translation, 6, 115-120.
• Georgakopoulou, P. (2019). Template files: The Holy Grail of subtitling. Journal of Audiovisual Translation, 2(2),137-160.
• 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 (RIDU), 15(1). http://dx.doi.org/10.19083/ridu.2021.1213
• Guerberof-Arenas, A. (2009). Productivity and quality in MT post-editing. In Proceedings of the MT Summit XII Workshop Beyond Translation Memories: New Tools for Translators MT.
• Guerberof-Arenas, A. (2013). What do professional translators think about post-editing. The Journal of Specialised Translation, 19(19), 75-95.
• Karakanta, A. (2022). Experimental research in automatic subtitling: At the crossroads between Machine Translation and Audiovisual Translation. In G. M. Greco, A. Jankowska & A. Szarkowska (Eds.), Methodological Issues in Experimental Research in Audiovisual Translation and Media Accessibility, Translation Spaces 11(1), 89-112. https://doi.org/10.1075/ts.21021.kar
• Karakanta, A., Bentivogli, L., Cettolo, M., Negri, M. & Turchi, M. (2022). Post-editing in Automatic Subtitling: A Subtitlers’ perspective. In Proceedings of the 23rd Annual Conference of the European Association for Machine Translation (pp. 261-270). European Association for Machine Translation. https://aclanthology.org/2022.eamt-1.29.pdf
• Kenny, D. & Doherty. S. (2014). Statistical machine translation in the translation curriculum: overcoming obstacles and empowering translators. The Interpreter and Translator Trainer, 8(2), 276-294.
• Kenny, D. (2022). Machine translation for everyone: Empowering users in the age of artificial intelligence. Language Science Press. http://10.5281/zenodo.6653406
• Koponen, M., Sulubacak, U., Vitikainen, K. & Tiedemann, J. (2020). MT for subtitling: Investigating professional translator’s user experience and feedback. In Proceedings of 1st Workshop on Post-Editing in Modern-Day Translation. Virtual. Association for Machine Translation in the Americas (pp. 79-92).
• Krings, H. P. (2011). Repairing texts: empirical investigations of machine translation post-editing processes. The Kent University Press.
• Läubli, S., Fishel, M., Massey, G., Ehrensberger-Dow, M. & Volk, M. (2013). Assessing Post-Editing Efficiency in a Realistic Translation Environment. In S. O’Brien, M. Simard & L. Specia (Eds.), Proceedings of MT Summit XIV Workshop on Post-editing Technology and Practice (pp. 83-91). European Association for Machine Translation. https://doi.org/10.5167/uzh-80891
• Lionbridge (2022, August 23). Lionbridge Language Cloud: Is Machine Translation getting better? The Lionbridge Team. https://www.lionbridge.com/blog/translation-localization/language-cloud-is-machine-translation-getting-better/
• Lommel, A., Uszkoreit, H. & Burchardt, A. (2014). Multidimensional Quality Metrics (MQM): A Framework for Declaring and Describing Translation Quality Metrics. Revista Tradumàtica. Tecnologies de la Traducció, 12, 455-463.
• Martín-Mor, A. & Sánchez-Gijón, P. (2016). Machine translation and audiovisual products: a case study. The Journal of Specialised Translation, 26, 172-186.
• Martínez Martínez, J. M. & Vela, M. (2016). SubCo: A Learner Translation Corpus of Human and Machine Subtitles. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16) (pp. 2246-2254). European Language Resources Association (ELRA). https://aclanthology.org/L16-1357.pdf
• Matusov, E., Wilken, P., & Georgakopoulou, Y. (2019). Customizing neural machine translation for subtitling. In Proceedings of the Fourth Conference on Machine Translation (WMT), Volume 1 Research Papers (pp. 82-93). Association for Computational Linguistics.
• 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
• Moorkens, J., Toral, A., Castilho, S., & Way, A. (2018). Translators’ perceptions of literary post-editing using statistical and neural machine translation. Translation Spaces, 7(2), 240-262. https://doi.org/10.1075/ts.18014.moo
• Nunes Vieira, L. & Alonso, E. (2018). The use of machine translation in human translation workflows: Practices, perceptions and knowledge exchange. Technical report. University of Bristol and Universidad Pablo de Olavide.
• O’Curran, E. (2014). Translation quality in post-edited versus human-translated segments: a case study. In S. O’Brien, M. Simard & L. Specia (Eds.), Proceedings of AMTA Third Workshop on Post-editing technology and Practice (pp. 113-118). Association for Machine Translation in the Americas.
• Ortiz-Boix, C. (2016). Machine translation and post-editing in wildlife documentaries: Challenges and possible solutions. Hermeneus: Revista de la Facultad de Traducción e Interpretación de Soria, 18, 269-313.
• Parra Escartín, C. (2018). ¿Cómo ha evolucionado la traducción automática en los últimos años? La linterna del traductor, 16, 20-28.
• Pedersen, J. (2017). The FAR model: assessing quality in interlingual subtitling. The Journal of Specialised Translation, 28, 210–229.
• Petukhova, V., Agerri, R., Fishel, M., Georgakopoulou, Y., Penkale, S., del Pozo, A., Sepesy M., Volk, M. & Way, A. (2012). SUMAT: Data Collection and Parallel Corpus Compilation for Machine Translation of Subtitles. In Proceedings of the 8th Language Resources and Evaluation Conference (pp. 21-28).
• Quesada-Granja, C. (2009, January 19). Distribución por longitud de las palabras de diferentes idiomas. Slideshare. http://www.slideshare.net/quesadagranja/distribucin-por-longitud-de-las-palabras-de-diferentes-idiomas-presentation
• Rico, C. & González Pastor, D. (2022). The role of machine translation in translation education: A thematic analysis of translator educators’ beliefs. The international Journal of Translation & Interpreting, 14(1), 177-197.
• Rinsche, A. & Portera-Zanotti, N. (2009). Study report to the Directorate General for Translation of the European Commission. Final Version. Study on the Size of the Language Industry in the EU. The Language Technology Centre Ltd.
• Romero-Fresco, P. & Martínez, J. (2015). Accuracy Rate in Live Subtitling: The NER model. In R. B. Piñero & J. Díaz-Cintas (Eds.), Audiovisual Translation in a Global Context. Palgrave Studies in Translating and Interpreting (pp. 28-50). Palgrave Macmillan. https://doi.org/10.1057/9781137552891_3
• Romero-Fresco, P. & Pöchhacker, F. (2017). Quality assessment in interlingual live subtitling: the NTR model. Linguistica Antverpiensia, New Series: Themes in Translation Studies, 16, 149-167. https://doi.org/10.52034/lanstts.v16i0
• Sagar, R. (2020, June 5). Netflix Is Using AI For Its Subtitles. Aim. https://analyticsindiamag.com/netflix-ai-subtitles-transalation/
• Sakamoto, A. (2021). The value of Translation in the Era of Automation: An examination of Threats. In R. Desjardins, C. Larsonneur & P. Lacour (Eds.), When Translation Goes Digital (pp. 231-256). Palgrave Studies in Translating and Interpreting MacMillan.
• Sánchez-Gijón, P. (2016). La posedición: hacia una definición competencial del perfil y una descripción multidimensional del fenómeno. Sendebar, 27, 151-162. https://doi.org/10.30827/sendebar.v27i0.4016
• Szarkowska, A., Díaz-Cintas, J. & Gerber-Morón, O. (2021). Quality is in the eye of the stakeholders: what do professional subtitlers and viewers think about subtitling? Universal Access in the Information Society, 20, 661-675. https://doi.org/10.1007/s10209-020-00739-2
• Translation Automation User Society (TAUS) (2010). Machine Translation post-editing guidelines. De Rijp.
• Torres-Hostench, O., Presas, M. & Cid-Leal, P. (coords.) (2016). El uso de traducción automática y posedición en las empresas de servicios lingüísticos españolas: Informe de investigación ProjecTA 2015. https://ddd.uab.cat/record/148361
• Varga, C. (2021). Online Automatic Subtitling Platforms and Machine Translation. An Analysis of Quality in AVT. Scientific Bulletin of the Politechnica University of Timişoara, 20(1), 37-49.
• Vercauteren, G., Reviers, N. & Steyaert, K. (2021). Evaluating the effectiveness of machine translation of audiodescription: the results of two pilot studies in the English-Dutch language pair. Revista Tradumàtica. Tecnología de la Traducción, 19, 226-252.