Kontrastive Analyse maschinell generierter Fachtranslate (EN-DE) im Strafrecht

Abstract This article analyses and compares two texts produced via neural machine translation (NMT). It describes potential problems concerning lexical, syntactical and textual aspects and potential strategies for legal translation from English to German with reference to a blog text on criminal law authored by a US law firm. The text is part of the teaching material in a legal translation course of the Master’s program in Multilingual Specialized Communication and Specialized Translation (MA FKÜ) at the Institute of Translation and Multilingual Communication (ITMK) at the TH Köln – University of Applied Sciences. For this purpose, translations produced by DeepL and ChatGPT (more specifically the didactic interface used at the TH Köln, THKI GPT-Lab) are analysed with a focus on specific legal questions and the issue of legal comparison which is fundamental to legal translation. Finally, this comparison leads to a recommendation on the use of these tools.