The Register Variation in Translated Epidemic Prevention Manuals as Emergency Language Services

The Register Variation in Translated Epidemic Prevention Manuals as Emergency Language Services

Yukai Hu, Wenjing Zhang, Yike Gao
DOI: 10.4018/IJTIAL.313920
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Abstract

Using Biber's MD model, this paper investigates the register variation in crisis translation and discovers that learned exposition is the text type that comes closest to crisis translation. Crisis translation has “explicit” and “informational” features, according to statistics. When compared to the non-translational “learned and scientific” corpus, the translated corpus includes feature of “nominalization.” Furthermore, the researchers discovered that in Biber's MD model, the variables AWL and PHC had a strong liner connection with NOMZ.
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Introduction

According to previous studies, native and non-native varieties of English, as well as translated English, have different registers (Kruger and Van Rooy, 2018). Explicitation, normalization or conventionalization, simplification, and homogenization are all common features of translated language (Kruger, and Van Rooy, 2016). With the advancement of translation technology, a large number of technological components are now involved in the production of translations. Neural Machine translation and post-editing, crowdsourcing translation trends, and Web 2.0-based translation for specific purposes are all new things that are influencing translation currently. Kruger investigated the the explicitation performance of Neural Machine Translation and found that this new Machine Translation Architecture to some extent have possesses “contextual awareness” (Krüger, 2020). Web 2.0 has spawned a new form of translation—crowdsourcing, which is still a rather young field. There are some studies on the quality and perception of crowdsourcing translation. For example, Jimenez-Crespo (2017) finds a dynamic conceptualization of translation quality due to economic considerations, in which translation quality evolves from static to dynamic approaches. Dolmaya (2012) uses an online survey of Wikipedia volunteer translators to examine participants’ perceptions of translation under crowdsourcing translation from a sociological perspective. Technology advancements not only influenced translation in general, but also changed the translation industry. Due to the Covid-19 pandemic, language emergency service has highlighted its importance in enhancing communication between doctors and patients at home and in preventing and controlling the importation of foreign epidemics.

Translation technologies are closely relevant to disaster management and emergency language service. However, the importance of multilingual communication in catastrophes and emergencies, as well as the function of translation and interpretation in aiding this, has received little emphasis (O’Brien, 2019). With the acceleration of globalization, “translation of language” has also become a major part of language emergency service as well as an important part of language emergency studies in various countries.

These studies mainly give their attention on the following aspects: first, the negative consequences of the lack of language translation services and the coping strategies. Federici (2020) explored the importance of emergency translation services in a multilingual context. Currently, the provision of translation services (e.g., the release of crisis-related multilingual information) generally stays in the crisis response phase, i.e., during the crisis; whereas the authors argue that language translation should be viewed as part of disaster prevention efforts and contingency planning and carried out throughout the crisis management process. Second, the important role of language translation in emergencies. For example, Cadwell (2015) discusses, in the form of interviews, the important role played by translators in earthquake news broadcasts, nuclear leak information releases, and government emergency response procedures. Third, there are studies on improving the quality of language services. For example, Skøt (2017) discusses suggestions for countermeasures for hearing-impaired people in Denmark seeking medical and psychological services after a disaster from the perspective of problems in accessing interpretation services, etc. Cadwell (2019) argues that crisis interpreting is a kind of context-rich interpreting.

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