Translation competences

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Back to the integration of MT and HT which is predominating the workflow in the translation industry day by day, Yamada (2018, para. 1) has pointed out that the assumption behind the MT+PE model is that the competences of the machine and those of the human are complementary, but this assumption is no longer valid. The reason is that technological advances have created NMT systems that more closely mimic HT, including human-like errors, “thus increasing the effort required for post-editors to detect and correct errors” (para. 1). Yamada (2019, p. 87) also concludes that NMT+PE does not contribute to reducing the post-editors’ cognitive effort or error correction rate and that NMT+PE requires almost the same competence as ordinary HT. Although Yamada’s (2019) experiment involved college students who might arguably be less familiar with the task, the present author observes that the NMT+PE model poses the same challenges in a professional setting.

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pp. 208-209). As its indicator of translation competence, PACTE adopted acceptability to define translation product quality based on whether or not a translation effectively communicates (a) the meaning of the ST; (b) the function of the translation; and (c) makes use of appropriate language (PACTE, 2009, pp. 210-217).

Thus, the acceptability of the translations produced by the college students employed by Yamada (2019) was expected to be low compared to those of professional translators as they were thought to need more training, experience, and self-learning to gain the competences just described. Based on PACTE’s model of translation competence and translation competence acquisition, Castillo (2015) conducted an experiment to observe how the acceptability of translations evolves throughout the process of acquiring translation competence, employing translation students and recent graduates as participants with a focus on EN to Spanish translation. The preliminary results showed no firm conclusions. Employing professional translators for experimental research in an academic setting is considered to be difficult as it entails greater cost even if the result approximates better to reality.

The EMT expert group was set up by the Directorate-General for Translation in April 2007. Its main task is to make specific proposals with a view to implementing a European reference framework for a Master's in translation (European Master's in Translation – EMT) throughout the European Union. EMT (2009) defines competence as the combination of aptitudes, knowledge, behavior, and know-how necessary to carry out a given task under given conditions. Moreover, this combination needs to be recognized and legitimized by a responsible authority such as an institution or an expert.

EMT (2009) proposed six types of competence: translation service provision competence, language competence, intercultural competence, information mining competence, thematic competence, and technological competence. Knowing the possibilities and limits of the MT+PE model (as discussed in Section 1.1.3) is considered as part of the technological competence (EMT, 2009, p. 7).

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ISO 17100:2015 is an internationally recognized standard for translation services and was created to respond to the market need for a universally accepted benchmark. It sets standards for achieving quality by following the translation process steps it defines.

According to the standard, translators should have six types of professional competences: (a) translation competence; (b) linguistic and textual competence in the source language and the target language; (c) competence in research, information acquisition, and processing; (d) cultural competence; (e) technical competence; and (f) domain competence. As for translator qualifications, the same standard requires that translators should meet at least one of the following criteria by having:

a) a recognized graduate qualification in translation from an institution of higher education;

b) a recognized graduate qualification in any other field from an institution of higher education plus two years of full-time professional experience in translating;

c) five years of full-time professional experience in translating.

The present study conducted three experiments that employed Chinese professional translators for translation and quality assessment tasks. All of these translators met either criterion b) or c) stated above. Below is a summary of the social background to the China translation industry revealed in a seminar organized by Japan Translation Federation (JTF, 2012), which attributes the difficulties of quality management in China’s translation industry to translators’ lack of training, social status, and remuneration. These shortcomings have a detrimental impact on Japan’s translation industry since translation companies in Japan often work with translation companies or translators based in China for the purpose of cost reduction. To the present author’s

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knowledge, China branches of many Japanese enterprises also employ local translation vendors or in-house translators for their translation needs.

a) Lack of social status: Translation Studies is yet to be established as an academic discipline in China, and the social status of translators is extremely low. The importance of translation/interpreting is not acknowledged by society. Translation is deemed to be a practice of replacing STs with TTs on a word level, and anyone can translate if there is a dictionary at hand.

b) Lack of remuneration: translation as a profession is yet to be established in China. As a profession, there is no clear line between translation and interpreting. The same word ^翻译 can be used to refer to both translators and interpreters. Most importantly, one cannot make a living if working only as a translator. In most cases, part-time translators have other professions as their daily job.

c) Lack of management: most translation agencies are small scale ones. The average number of translators they employ is around ten, and the people who run the company often do not understand what translation is. This suggests that translators cannot acquire proper training or management in the process of exercising translation.

d) Lack of training: most students who major in Japanese language become translators after learning JA in universities for only 3.5 years. Translators who are skilled in JA and equipped with specialized knowledge are scarce.

Thus, because of the difference in social, industrial, educational, and institutional environments, the translational competence of a professional translator in China who can meet one of the three criteria specified by ISO 17100:2015 is very likely to be markedly different from that of a professional translator in the European Union. With

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such a difference as a given, LSPs and buyers can be more understanding of generally low JA to ZH-CN translation quality, and they should think about what measures can be taken to improve the current situation.

The same observation can be seen in TAUS (2017a, p. 10) which points out that

“many people in the human translation (HT) space say translators are not good enough to tackle today’s challenges, and more and more errors are detected than in the past,”

implying that ZH-CN may not be an exception.

All of the observations just reported strengthen the rationale for source optimization. As suggested by Lommel (2016), optimized source content can help translators produce better quality. In addition, it will lower the risk of poor outcomes and help buyers achieve their ultimate goal. Despite the growing conviction that optimized source will help both translators and buyers, precisely how to optimize source content remains an area under-researched in the academic domain and a topic with which both LSPs and buyers are struggling, especially when it comes to JA.

Kelly (2010, p. 1) asserts that “poorly constructed text is notoriously difficult to translate, but the definition of good writing may vary from one language to another.”

While general guidelines for specific languages (see Section 2.4) are available on the market, Kelly (2010) suggests that having a non-native speaker review source language texts can make the texts more translation-friendly as the non-native speaker can identify what might be difficult to express in another language. His reasoning is that the more input authors can obtain from individuals who are able to read the content from the standpoint of a non-native speaker, the better suited the content will be for global audiences. Moreover, writing text that is more “translatable” from the start will enable more people in more languages to understand the message authors originally intended to convey. On this basis, translators who are Chinese-speakers are considered to be suitable candidates for identifying problematic features in JA STs.

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The other best practice explained by Kelly (2010) is "for translators to provide feedback to content creators in order to better inform their process in the future."

However, asking LSPs or freelance translators to provide a report on the challenges faced when translating the content is not realistic for various reasons. First, it entails additional cost and time. Second, translators do not necessarily have the expertise (i.e., a framework or meta-language) to evaluate ST quality and articulate issues in the source content. Third, capturing translator feedback and systematically incorporating it into authoring rules can be difficult for content creators if they have no support.

Therefore, this study proposes a systematic set of writing rules as a reference for JA authors in writing for a global audience with a view to achieving improved quality and decreased time and cost. These rules can be viewed as originating from systematic feedback from a professional translator, articulating the difficulties in ZH-CN translation induced by problematic JA source features and providing alternative expressions for reference.

In the scenario addressed by the present study, the STs have already been written.

Therefore, it is a question of rewriting the STs to make them more translation-friendly to human translators, a process akin to pre-editing through which NTIs are removed from STs in order to generate better MT output (Pym, 2019, p. 443).

Hutchins and Somers (1992, p. 151) define pre-editing as “checking source texts for foreseeable problems for the system and trying to eradicate them,” which may involve applying a controlled language to radically reform texts. This study adopts the principles expressed in Hutchins and Somers’ definition of pre-editing, that is, both identification of problems in STs and rewriting of problematic STs with alternative expressions. However, it should be noted that in the present study these principles are applied to source optimization for HT. (See Section 2.3.1 for a wider discussion of these principles from the perspective of text simplification and adaptation.)

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