Enhancing Global Biotechnology Collaboration: Effective Chinese to English Translation Strategies for Medical and Biotechnological Communication

Abstract

This paper introduces a novel method for the accurate translation of medical and biotechnological terms from Chinese to English, addressing a crucial need within global biotechnology collaboration. The method employs advanced linguistic analysis and machine learning techniques, leveraging a cyclic neural network to generate phonetic representations of complex biotechnological terms. This approach not only preserves the syntactic structure and linguistic style but also ensures the semantic integrity of the translated terms. The process begins with the generation of phonetic symbols for the original Chinese terms, followed by segmentation based on the principle of minimum entropy. These segments are then converted into corresponding English terms, with a focus on maintaining technical accuracy. The final step involves integrating these terms into coherent English translations. The reliability of these translations is subsequently evaluated through systematic methods, including automated standard assessments and screening, to ensure they meet the stringent requirements of biotechnological communication. This technique is designed to enhance communication clarity and accuracy in international biotechnological environments, facilitating better understanding and collaboration across linguistic barriers. The study highlights the potential of this translation method to significantly impact the dissemination and application of biotechnological knowledge globally.