MT vs HT.docx

Digitalization and the widespread applications of artificial intelligence (AI) have significantly transformed the field of translation, offering both opportunities for increased efficiency and challenges in the context of maintaining accuracy, cultural nuances, and terminological precisions. Within the domain of business, machine translation (MT) plays a crucial role in translating business texts, enabling faster communication across global markets. Despite the advancements in MT, human intervention is often required to address challenges such as terminology accuracy, tone, and cultural appropriateness in business translation. The aim of this article is to explore and analyze the opinions and experiences of professional translators regarding the use of MT tools in translating business texts. Our objective is to assess the challenges, errors, and strategies employed by translators when working with MT, as well as to investigate the post-editing tasks necessary to enhance the quality of machine-generated translations. The main issues of the research are the limitations of MT in accurately translating specialized business terminology, the challenges of maintaining consistency in terminology across documents, and the difficulty in capturing the intended tone, style, and cultural nuances of business texts. This research then explores the perspectives of professional translators about the use of machine translation tools for business text translation. The study is based on a survey conducted among university professors teaching in “Translation Studies” Degree Programs, freelance translators, and senior year students enrolled in those programs.