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Papers by Rocío Caro Quintana

Research paper thumbnail of Integration of Machine Translation and Translation Memory: Post-editing efforts

The development of Translation Technologies, like Translation Memory and Machine Translation, has... more The development of Translation Technologies, like Translation Memory and Machine Translation, has completely changed the translation industry and translator's workflow in the last decades. Nevertheless, TM and MT have been developed separately until very recently. This ongoing project will study the external integration of TM and MT, examining if the productivity and post-editing efforts of translators are higher or lower than using only TM. To this end, we will conduct an experiment where translation students and professional translators will be asked to translate three short texts; then we will check the post-editing efforts (temporal, technical and cognitive efforts) and the quality of the translated texts.

Research paper thumbnail of Translation Quality Assessment: From Principles to Practice

Language Value, 2020

This is the first volume that brings together research and practice from academic and industry se... more This is the first volume that brings together research and practice from academic and industry settings and a combination of human and machine translation evaluation. Its comprehensive collection of papers by leading experts in human and machine translation quality and evaluation who situate current developments and chart future trends fills a clear gap in the literature. This is critical to the successful integration of translation technologies in the industry today, where the lines between human and machine are becoming increasingly blurred by technology: this affects the whole translation landscape, from students and trainers to project managers and professionals, including in-house and freelance translators, as well as, of course, translation scholars and researchers. The editors have broad experience in translation quality evaluation research, including investigations into professional practice with qualitative and quantitative studies, and the contributors are leading experts in their respective fields, providing a unique set of complementary perspectives on human and machine translation quality and evaluation, combining theoretical and applied approaches.

Research paper thumbnail of Integration of Machine Translation and Translation Memory: Post-editing efforts

Proceedings of the Translation and Interpreting Technology Online Conference TRITON 2021, 2021

Research paper thumbnail of Audiovisual Translation through NMT and Subtitling in the Netflix Series Cable Girls

Proceedings of the Translation and Interpreting Technology Online Conference TRITON 2021, 2021

In recent years, the emergence of streaming platforms such as Netflix, HBO or Amazon Prime Video ... more In recent years, the emergence of streaming platforms such as Netflix, HBO or Amazon Prime Video has reshaped the field of entertainment [1], which increasingly relies on subtitling, dubbing or voice-over modes [2] [3]. However, little is known about audiovisual translation when dealing with Neural Machine Translation (NMT) engines. This work-in-progress paper seeks to examine the English subtitles of the first episode of the popular Spanish Netflix series Cable Girls and the translated version generated by Google Translate and DeepL. Such analysis will help us determine whether there are significant linguistic differences that could lead to miscomprehension or cultural shocks. To this end, the corpus compiled consists of the Spanish script, the English subtitles available on Netflix and the translated version of the script. As regards data analysis, errors have been classified following the DQF/MQM Error typology and have been evaluated with the automatic BLEU metric. Results show that NMT engines offer good-quality translations, which in turn may benefit translators working with audiovisual entertainment resources.

Research paper thumbnail of Introducing linguistic transformation to improve translation memory retrieval. Results of a professional translators’ survey for Spanish, French and Arabic

Translation memory systems (TMS) are the main component of computer-assisted translation (CAT) to... more Translation memory systems (TMS) are the main component of computer-assisted translation (CAT) tools. They store translations allowing to save time by presenting translations on the database through matching of several types such as fuzzy matches, which are calculated by algorithms like the edit distance. However, studies have demonstrated the linguistic deficiencies of these systems and the difficulties in data retrieval or obtaining a high percentage of matching, especially after the application of syntactic and semantic transformations as the active/passive voice change, change of word order, substitution by a synonym or a personal pronoun, for instance. This paper presents the results of a pilot study where we analyze the qualitative and quantitative data of questionnaires conducted with professional translators of Spanish, French and Arabic in order to improve the effectiveness of TMS and explore all possibilities to integrate further linguistic processing from ten transformation types. The results are encouraging, and they allowed us to find out about the translation process itself; from which we propose a pre-editing processing tool to improve the matching and retrieving processes.

Research paper thumbnail of Audiovisual Translation through NMT and Subtitling in the Netflix Series Cable Girls

Proceedings of the Translation and Interpreting Technology Online Conference TRITON 2021, 2021

Research paper thumbnail of Book Review: Translation Quality Assessment: From Principles to Practice

Language Value

With the growth of digital content and the consequences of globalization, more content is publish... more With the growth of digital content and the consequences of globalization, more content is published every day and it needs to be translated in order to make it accessible to people all over the world. This process is very simple and straightforward thanks to the implementation of Machine Translation (MT), which is the process of translating texts automatically with computer software in a few seconds. Nevertheless, the quality of texts has to be checked to make them comprehensible, since the quality from MT is still far from perfect. Translation Quality Assessment: From Principles to Practice, edited by Joss Moorkens, Sheila Castilho, Federico Gaspari and Stephen Doherty (2018), deals with the different ways (automatic and manual) these translations can be evaluated. The volume covers how the field has changed throughout the decades (from 1978 until 2018), the different methods it can be applied, and some considerations for future Translation Quality Assessment applications.

Research paper thumbnail of Chapter 4. Semantic textual similarity based on deep learning

Benjamins Translation Library

Research paper thumbnail of Integration of Machine Translation and Translation Memory: Post-editing efforts

The development of Translation Technologies, like Translation Memory and Machine Translation, has... more The development of Translation Technologies, like Translation Memory and Machine Translation, has completely changed the translation industry and translator's workflow in the last decades. Nevertheless, TM and MT have been developed separately until very recently. This ongoing project will study the external integration of TM and MT, examining if the productivity and post-editing efforts of translators are higher or lower than using only TM. To this end, we will conduct an experiment where translation students and professional translators will be asked to translate three short texts; then we will check the post-editing efforts (temporal, technical and cognitive efforts) and the quality of the translated texts.

Research paper thumbnail of Translation Quality Assessment: From Principles to Practice

Language Value, 2020

This is the first volume that brings together research and practice from academic and industry se... more This is the first volume that brings together research and practice from academic and industry settings and a combination of human and machine translation evaluation. Its comprehensive collection of papers by leading experts in human and machine translation quality and evaluation who situate current developments and chart future trends fills a clear gap in the literature. This is critical to the successful integration of translation technologies in the industry today, where the lines between human and machine are becoming increasingly blurred by technology: this affects the whole translation landscape, from students and trainers to project managers and professionals, including in-house and freelance translators, as well as, of course, translation scholars and researchers. The editors have broad experience in translation quality evaluation research, including investigations into professional practice with qualitative and quantitative studies, and the contributors are leading experts in their respective fields, providing a unique set of complementary perspectives on human and machine translation quality and evaluation, combining theoretical and applied approaches.

Research paper thumbnail of Integration of Machine Translation and Translation Memory: Post-editing efforts

Proceedings of the Translation and Interpreting Technology Online Conference TRITON 2021, 2021

Research paper thumbnail of Audiovisual Translation through NMT and Subtitling in the Netflix Series Cable Girls

Proceedings of the Translation and Interpreting Technology Online Conference TRITON 2021, 2021

In recent years, the emergence of streaming platforms such as Netflix, HBO or Amazon Prime Video ... more In recent years, the emergence of streaming platforms such as Netflix, HBO or Amazon Prime Video has reshaped the field of entertainment [1], which increasingly relies on subtitling, dubbing or voice-over modes [2] [3]. However, little is known about audiovisual translation when dealing with Neural Machine Translation (NMT) engines. This work-in-progress paper seeks to examine the English subtitles of the first episode of the popular Spanish Netflix series Cable Girls and the translated version generated by Google Translate and DeepL. Such analysis will help us determine whether there are significant linguistic differences that could lead to miscomprehension or cultural shocks. To this end, the corpus compiled consists of the Spanish script, the English subtitles available on Netflix and the translated version of the script. As regards data analysis, errors have been classified following the DQF/MQM Error typology and have been evaluated with the automatic BLEU metric. Results show that NMT engines offer good-quality translations, which in turn may benefit translators working with audiovisual entertainment resources.

Research paper thumbnail of Introducing linguistic transformation to improve translation memory retrieval. Results of a professional translators’ survey for Spanish, French and Arabic

Translation memory systems (TMS) are the main component of computer-assisted translation (CAT) to... more Translation memory systems (TMS) are the main component of computer-assisted translation (CAT) tools. They store translations allowing to save time by presenting translations on the database through matching of several types such as fuzzy matches, which are calculated by algorithms like the edit distance. However, studies have demonstrated the linguistic deficiencies of these systems and the difficulties in data retrieval or obtaining a high percentage of matching, especially after the application of syntactic and semantic transformations as the active/passive voice change, change of word order, substitution by a synonym or a personal pronoun, for instance. This paper presents the results of a pilot study where we analyze the qualitative and quantitative data of questionnaires conducted with professional translators of Spanish, French and Arabic in order to improve the effectiveness of TMS and explore all possibilities to integrate further linguistic processing from ten transformation types. The results are encouraging, and they allowed us to find out about the translation process itself; from which we propose a pre-editing processing tool to improve the matching and retrieving processes.

Research paper thumbnail of Audiovisual Translation through NMT and Subtitling in the Netflix Series Cable Girls

Proceedings of the Translation and Interpreting Technology Online Conference TRITON 2021, 2021

Research paper thumbnail of Book Review: Translation Quality Assessment: From Principles to Practice

Language Value

With the growth of digital content and the consequences of globalization, more content is publish... more With the growth of digital content and the consequences of globalization, more content is published every day and it needs to be translated in order to make it accessible to people all over the world. This process is very simple and straightforward thanks to the implementation of Machine Translation (MT), which is the process of translating texts automatically with computer software in a few seconds. Nevertheless, the quality of texts has to be checked to make them comprehensible, since the quality from MT is still far from perfect. Translation Quality Assessment: From Principles to Practice, edited by Joss Moorkens, Sheila Castilho, Federico Gaspari and Stephen Doherty (2018), deals with the different ways (automatic and manual) these translations can be evaluated. The volume covers how the field has changed throughout the decades (from 1978 until 2018), the different methods it can be applied, and some considerations for future Translation Quality Assessment applications.

Research paper thumbnail of Chapter 4. Semantic textual similarity based on deep learning

Benjamins Translation Library