How to Become a Patent Translator: Tricks and Tips – Notions of Text Genre and Ceremony to the Rescue

Avant d’entreprendre la traduction de brevets et d’abrégés de brevets, les traducteurs, qui ne peuvent se dire experts d’un domaine spécifique, doivent tenir compte du contexte de production des genres textuels ainsi que des intentions communicatives, afin de s’assurer que le sens est rendu de façon acceptable (compte tenu de la cérémonie), de façon à ne choquer personne ni dénaturer l’objectif de l’auteur. Le présent article fait état des résultats d’une étude dans laquelle ont été analysées les séquences rhétoriques (moves) des abrégés de brevets dans quatre langues (chinois, espagnol, français et anglais) et dans quatre domaines (médecine, chimie, télécommunications et informatique), ainsi que la valeur rhétorique des choix linguistiques (par ex. : modalité, temps verbaux, voix passive, adverbes et adjectifs). La méthodologie déployée est double : qualitative, pour expliquer le contexte de production des textes selon certains paramètres en rapport avec le genre et offrir une interprétation des résultats quantitatifs ; quantitative, pour appliquer l’analyse linguistique aux abrégés de brevets. L’échantillonnage de textes se fonde sur des critères de date de publication, de langue originale et de discipline, et a permis de constituer un corpus de 200 textes. Les résultats semblent indiquer, d’une part, que la discipline ne joue pas un rôle considérable dans les choix linguistiques des rédacteurs et, d’autre part, que l’intensification et l’atténuation sont toutes deux des procédés rhétoriques visant à combiner intentions privées et finalités collectives, afin de satisfaire les exigences institutionnelles et les attentes des destinataires.Before starting to translate patents and patent abstracts, translators – who are not discipline experts – need to be aware of the context of text genre production and the communicative purposes and intentions to make sure they are conveying the intended meaning in the accepted manner (of the typical ceremony) in order not to shock the recipient and distort the author’s original intent. This article aims to present the results of a study that analyzes both the moves of original patent abstracts in four languages (Chinese, Spanish, French and English) and four disciplines (medicine, chemistry, telecommunications, and IT) and the rhetorical value of linguistic choices (i.e., modality, verb tense, passive voice, adverbs and adjectives). The methodology used is twofold: qualitative so as to explain the text production context according to certain parameters related to text genre and give a better interpretation to the quantitative results, and quantitative so as to conduct a linguistic analysis of the patent abstracts. Text samples were chosen according to date of publication, original language and discipline, and form a corpus of 200 texts. The results appear to show that discipline does not play a major role in the linguistic choices made by the abstractors, and that boosting and hedging are both rhetorical ways to combine private intentions and collective purposes, while satisfying institutional requirements and recipients’ expectations

On the Complementarity between Human Translators and Machine Translation

Many translators are fearful of the impact of Machine Translation (MT) on their profession, broadly speaking, and on their livelihoods more specifically. We contend that their concern is misplaced, as human translators have a range of skills, many of which are currently – with no signs of any imminent breakthroughs on the horizon – impossible to replicate by automatic means. Nonetheless, in this paper, we will show that MT engines have considerable potential to improve translators’ productivity and ensure that the output translations are more consistent. Furthermore, we will investigate what machines are good at, where they break down, and why the human is likely to remain the most critical component in the translation pipeline for many years to come

On the complementarity between human translators and machine translation

Many translators are fearful of the impact of Machine Translation (MT) on their profession, broadly speaking, and on their livelihoods more specifically. We contend that their concern is misplaced, as human translators have a range of skills, many of which are currently – with no signs of any imminent breakthroughs on the horizon – impossible to replicate by automatic means. Nonetheless, in this paper, we will show that MT engines have considerable potential to improve translators’ productivity and ensure that the output translations are more consistent. Furthermore, we will investigate what machines are good at, where they break down, and why the human is likely to remain the most critical component in the translation pipeline for many years to com