Human Translator

Human translation research focuses on improving the accuracy, efficiency, and cultural sensitivity of translation processes, both human and machine-assisted. Current research explores leveraging large language models (LLMs) like GPT-4 to enhance translation quality, particularly for challenging tasks such as idiom translation and handling rare words, while also investigating how to better integrate human expertise and decision-making processes into machine translation systems. This work is significant because it aims to improve the quality and speed of translation across various domains, from literary works to technical documents and video games, ultimately bridging communication gaps and facilitating cross-cultural understanding. Furthermore, research is actively developing methods to assess translator reliability and automatically correct errors in human translations, leading to more efficient and effective workflows.