1. INTRODUCTION
1.2. T HEORETICAL F RAMEWORK AND R ESEARCH B ACKGROUND
1.2.1. Translation of Documentaries through Voice-‐Over and Off-‐Screen Dubbing 26
Implementing Machine Translation and Post-Editing to the Translation of Wildlife from 4 online bibliographies: Translation Studies Bibliography (John Benjamins)
<http://www.benjamins.com/online/tsb>1, Translation Studies Abstracts and
Bibliography of Translation Studies (St. Jerome)
<http://www.stjerome.co.uk/tsaonline/index.php>2, and Bibliografia de Traducció i d’Interpretació, BITRA, (Javier Aixelà, Universitat d’Alicante)
28 Chapter 1. Introduction sequences with dialogues (interviewers/interviewees) or monologues (talking heads). She also determines as important to leave a few seconds at the beginning
Implementing Machine Translation and Post-Editing to the Translation of Wildlife
30 Chapter 1. Introduction documentaries should be translated similarly to technical and scientific texts and having into account the different degrees of specialization one can find. Other aspects that are addressed by the authors are the variety of registers used within a same documentary or the synchrony, which are considered problematic. Espasa (2004) also highlights the interplay between image and sound and between verbal and non-‐verbal elements found in a documentary. And remarks the antithesis between documentaries and texts if assuming that documentaries are audiovisual by nature and texts are surmised to be written.
Matamala (2009a), on the other hand, carries out a descriptive study based on her professional experience translating wildlife documentary films and concludes that the some important features of the translation of documentaries are:
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Documentaries through Voice-Over and Off-Screen Dubbing 31
(1) The working conditions of the translators, as they are to work against the clock, which affects the documentation process. There may be a lack of postproduction scripts or, if they are available, they are of poor quality, having errors, inaccuracies and linguistic inconsistencies (also in Franco et al., 2010).
(2) the speakers and translation modes; meaning that, as there are different types of speakers and several techniques are used when translating a documentary, several transfer modes can be found within a same documentary.
(3) terminology, as some documentaries could be considered semi-‐
specialized texts, which means that translators need to do research and terminological searches in specialized areas (also in Matamala, 2010).
These characteristics, along with the characteristics of VO and OD presented earlier on this subsection, set the basis of the first article comprised in this PhD, which contains more information on the features presented above.
1.2.2. Machine Translation and Post-Editing
Research on MT started over 50 years ago with a clear goal: create a full automatic MT engine that could produce high quality translation, aka Full-‐
Automatic High Quality Translation (Bar-‐Hillel, 1960). The publication of the ALPAC report in 1966, which claimed that the quality of the MT engines built so far was low and gave no perspectives of improvement, caused the termination of funding devoted to the research on MT. In the 1980's an alternative approach was taken: computers were to be used as tools for the translators instead of being an alternative to them. Since then, great improvements have been made and the implementation of MT into the translation process has been proven particularly successful in domain specific texts, which guarantees translation of better quality
32 Chapter 1. Introduction
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2014), and on the experience of the post-‐editor, the usage of in-‐domain MT systems or the pre-‐editing of the source text (García, 2011).
PE could be defined as the human correction of an automatically translated text –raw machine translation– until the translation is acceptable according to a set of specifications. It could be classified in different groups depending on basically four aspects:
(1) Use of a source text:
1. Bilingual post-‐editing or post-‐editing: a post-‐editor corrects the machine translation comparing it to the source text.
2. Monolingual post-‐editing: a post-‐editor corrects the machine translated text without having access to the source text.
(2) Person performing the task:
1. Professional post-‐editing: a professional translator or post-‐editor corrects the machine translated text.
2. Non-‐professional crowd-‐sourced post-‐editing: users of certain forums or social media correct machine translated user generated content for information purposes.
(3) Purpose of the translation:
1. Informative post-‐editing: a post-‐editor corrects a machine translated text for information or in-‐company purposes, which do not require a high-‐quality translation.
2. Ready-‐to-‐publish post-‐editing: a post-‐editor corrects a machine translation for publishing purposes, which requires high quality.
34 Chapter 1. Introduction
(4) Level of intervention required:
1. Light or rapid post-‐editing: a post-‐editor checks the translation to guarantee it contains no mistranslations or offensive content.
2. Medium or minimal post-‐editing: a post-‐editor corrects the machine translation by ensuring its meaning and readability.
3. Full post-‐editing: a post-‐editor corrects the machine translation text guarantying it contains no grammar, fluency, terminology, style or voice problems.
The selection of one type of post-‐editing or another inevitably impacts both the quality of the final product and the effort required to carry out the post-‐editing task. This dissertation intends to analyze the effort required to post-‐edit a wildlife documentary that is ready to send to the dubbing study –aka ready to publish–, as well as to assess its quality. Hence, in order to accomplish the main objective of this PhD, the participants of the experiment were asked to perform a bilingual, professional, ready-‐to-‐publish, and full post-‐editing.
Effort has been a key research issue in the field of PE since the beginning of the 2000’s, mainly thanks to studies such as Krings (2001), Martínez (2003), O’Brien (2004, 2005 and 2006), Englund Dimitrova (2005), Carl et al. (2011), Tatsumi et al. (2012), Lacruz et al. (2014), or Almeida and O’Brien (2010), and Guerberof Arenas (2009), who compared PE effort and translation effort in order to determine which option is more feasible in terms of productivity. Results show that, in the majority of the cases, PE requires less effort than translation from scratch. Regarding PE effort, Specia (2011) researched the possibility to predict PE effort automatically by comparing sentences that were predicted to be of good or average quality. According to the results, sentences predicted as good quality are faster to post-‐edit than the others.
Krings (2001: 178) set the standard for the majority of the other works on this topic, including this PhD, by presenting a way to calculate PE effort. He
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divides PE effort into three categories: temporal effort –time required to post-‐edit a machine translated document–, technical effort –number of keystrokes, mouse movements, and mouse clicks needed to post-‐edited a machine translated