Human Translation

Human translation research focuses on improving the accuracy, fluency, and cultural appropriateness of automated translation systems, particularly for low-resource languages and specialized domains like literature and dialects. Current research leverages large language models (LLMs) and transformer architectures, exploring techniques like multi-agent collaboration, data augmentation (including synthetic data generation), and fine-tuning for specific tasks to enhance translation quality and address biases. This work is significant for bridging communication gaps across languages and cultures, impacting fields ranging from international business to education and accessibility for individuals with disabilities.