Traduire dans le domaine des technologies transformatrices: enjeux et difficultés, théorie et méthodologie
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Abstract
This doctoral thesis aims to study the specialized language of disruptive technologies (Big Data, Artificial Intelligence, and Blockchain), their terminology, and the challenges and opportunities related to English-French translation in this field.
In order to familiarize linguists and translators with this specialized discourse and provide them with a reliable terminological resource, we built 5-million-word text corpus hosted by Sketch Engine, and adopted an ECL-augmented lexicosemantic approach, with the Explanatory Combinatorial Lexicology (ECL) enriching terminology by leveraging the Government Pattern for describing the syntactic cooccurrence of terms, Lexical Functions for describing the lexical relationships of terms, and a more rigorous methodology for formulating lexicographic definitions. We then created an English-French glossary (the GLOTECHT, also available online) based on our corpus and a fine-tuned methodology. Finally, we tackled translation challenges, as well as issues regarding semantic taxonomic classification, lexicographic definitions, neology, polysemy, etc.
Description
This doctoral thesis aims to study the specialized language of disruptive technologies (Big Data, Artificial Intelligence, and Blockchain), and the challenges and opportunities related to English-French translation in this field.
The context of our study is marked by not only by a lack of academic contributions on the specialized discourse of disruptive technologies, coupled with a shortage of bilingual (English‒French) or multilingual lexicons dedicated to these technologies, but also by a very low proportion of publications in French (original texts and translations combined) in this area, which prevents a significant part of the world’s French-speaking community from accessing specialized knowledge in data science, AI, and blockchain. Therefore, it necessary to carry out large-scale translations in French, which can be achieved only if French-speaking linguists and translators are familiarized with the specialized language concerned and provided with the appropriate terminological resources.
Faced with this challenge, we have carried out our work following these steps: (i) creating a text corpus of some 5 million words, in line with the rules and principles of the corpus approach to terminology. By so doing, we have reevaluated existing methods for creating and exploiting comparable corpora, including techniques for analysing data on a modern platform (Sketch Engine). Likewise, we have highlighted the authenticity of the sources of terms, subtleties in their use by the community of specialists, and the terminological variation observed by experts in the specialized language under study; (ii) adopting an ECL-augmented lexico-semantic approach, with the Explanatory Combinatorial Lexicology (ECL) enriching terminology by leveraging the government pattern for describing the syntactic cooccurrence of terms, lexical functions for describing the paradigmatic and syntagmatic lexical relationships of terms, as well as a more rigorous methodology for formulating their lexicographic definitions; and (iii) building the GLOTECHT, our English-French glossary based on our corpus and a fine-tuned methodology. In the glossary, the ECL formalisms were simplified in order to tailor them to the specific needs of the users of our terminological resource, who are primarily technical translators, interpreters and editors, and thus may not master the formal apparatus of the ECL.
The thesis consists of 9 chapters and four appendices: (i) the nomenclature of the GLOTECHT, with its 214 entries distributed into semantic taxonomic classes; (ii) the GLOTECHT, whose electronic version is available online; (iii) the list of the texts constituting our corpus, distributed in two subcorpora (English and French); and (iv) the list of Lexical Functions mentioned in the thesis.
Keywords
technologies transformatrices, terminologie, traduction, Lexicologie explicative et combinatoire, corpus textuel