Balancing Machine and Human Learning in Translation
Peng Wang, David B. Sawyer · 2023
Learning entails forming a mental model and adjusting the parameters of the model. A significant characteristic of both human and machine learning is the capability to generalize new conclusions based on available observations. This chapter discusses the collective capability of ML technologies to facilitate personalized human learning and the importance of converting generic ML models to personalized tools that help humans acquire these technologies and translation-related knowledge and expertise. Examples include illustrating how ML can facilitate human learning by using vector space to visualize terminological schematic context (TSC), compiling source text-oriented comparable corpora, and building intelligent tutors.