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How to reinforce the translation sector
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THE SECTOR OF TRANSLATORS FOR PERFORMING ARTS NEEDS TO BE BETTER STRUCTURED This sector – which is a fairly recent addition to the translation family, but which is growing rapidly – can learn from its colleagues in the literary and audiovisual fields. A dialogue between
translators and theatre companies and venues should take place to better structure the sector and to develop a shared set of ‘basic rules’ for the performing arts sector, applicable to all EU countries and international players/platforms operating within the EU, setting a quality and working conditions framework that would substantially improve the theatre translation ecosystem.
The exercise of performing plays in the original language, accompanied by surtitles, aims to facilitate the circulation of works and to attract a wider audience, while preserving the profound singularity or cultural authenticity of the original.
01.6 | Machine and relay translation – practices affecting quality of translation EVEN THOUGH MACHINE TRANSLATION (MT) IS STILL UNSUITABLE FOR TRANSLATING LITERATURE, PROGRESS IN TECHNOLOGY SHOULD BE MONITORED CLOSELY MT is the process of substituting words in one language for those in another using computer software. It is a field of computational linguistics that has been developing since the mid-19th century, and has been developing rapidly in the last few years, with thousands of research articles published on the subject. There are different approaches to MT, based on their understanding of language itself, and the most popular current system is neural MT, which is the one used by Google Translate and DeepL.
The idea behind neural MT is not to translate word by word, but to use predictive computation to generate a new text in a different language. It is based not on dictionaries or grammatical rules, but on statistical analysis and the use of semantic maps. It is based on corpora, that is collections of written and spoken material that the software can use to extract results. This technology might seem promising, but MT is still unsuitable for translating literature (58). Firstly, MT makes many mistakes. Some are typical, others are more unpredictable, so the result is not publishable and human post-editing is needed to achieve an acceptable level. In the case of essays and academic papers, the results are getting better, but the generated texts still need human intervention.
58 https://actualitte.com/article/103055/interviews/des-livres-traduits-par-des-robots-quid-de-la-sensibilite
