Empirical Translation Process Research: Past and Possible Future
  Perspectives
Michael Carl
Over the past four decades, efforts have been made to develop and evaluate
models for Empirical Translation Process Research (TPR), yet a comprehensive
framework remains elusive. This article traces the evolution of empirical TPR
within the CRITT TPR-DB tradition and proposes the Free Energy Principle (FEP)
and Active Inference (AIF) as a framework for modeling deeply embedded
translation processes. It introduces novel approaches for quantifying
fundamental concepts of Relevance Theory (relevance, s-mode, i-mode), and
establishes their relation to the Monitor Model, framing relevance maximization
as a special case of minimizing free energy. FEP/AIF provides a mathematically
rigorous foundation that enables modeling of deep temporal architectures in
which embedded translation processes unfold on different timelines. This
framework opens up exciting prospects for future research in predictive TPR,
likely to enrich our comprehension of human translation processes, and making
valuable contributions to the wider realm of translation studies and the design
of cognitive architectures.