Empirical translation process research

Abstract

Over the last four decades, considerable efforts have been devoted to the modeling and evaluation of human translation processes. This article takes a closer look at the evolution of empirical Translation Process Research (TPR) within the CRITT TPR-DB tradition. It contends that human translation unfolds on various processing levels and puts forth the Free Energy Principle (FEP) and Active Inference (AIF) as a promising framework for modeling these intricately embedded processes in a mathematically rigorous framework. The article introduces innovative methods for quantifying fundamental concepts of Relevance Theory (relevance, s-mode, and i-mode translation) and establishes their connection with the Monitor Model, framing relevance maximization as a special case of free energy minimization. The framework presents exciting prospects for future research in predictive TPR, promising to enhance our understanding of human translation processes and contributing significantly to the broader field of translation studies and cognitive sciences in general.