Performance of Google Translate in Translating Commercial Contracts: Linguistics Errors Analysis

Abstract

The study investigates the effectiveness of Google Translate (GT) in translating five commercial contracts from English to Vietnamese, focusing on the identification and analysis of linguistic errors. The research employs a systematic approach to assess translation quality, utilizing quantitative methods to classify errors into categories icluding Sense (SENS), Terminology (TERM), Clarity (CL), and Reference Documents (RD). The findings reveal that TERM errors are the most prevalent, accounting for 30.91% of total errors, followed by CL errors at 19.39%. The study highlights GT's challenges in accurately interpreting technical terms and maintaining clarity, which are crucial for legal documents. It emphasizes the necessity of post-editing by human translators to enhance translation accuracy and reliability. The implications of this research are significant for translation students and professionals, as it provides insights into the limitations of machine translation and encourages the integration of human expertise in the translation process.