Toward a Behavioural Translation Style Space: Simulating the Temporal Dynamics of Affect, Behaviour, and Cognition in Human Translation Production

The paper introduces a Behavioural Translation Style Space (BTSS) that describes possible behavioural translation patterns. The suggested BTSS is organized as a hierarchical structure that entails various embedded processing layers. We posit that observable translation behaviour - i.e., eye and finger movements - is fundamental when executing the physical act of translation but it is caused and shaped by higher-order cognitive processes and affective translation states. We analyse records of keystrokes and gaze data as indicators of the hidden mental processing structure and organize the behavioural patterns as a multi-layered embedded BTSS. The BTSS serves as the basis for a computational translation agent to simulate the temporal dynamics of affect, automatized behaviour and cognition during human translation production.

An Active Inference Agent for Simulating Human Translation Processes in a Hierarchical Architecture: Integrating the Task Segment Framework and the HOF taxonomy

In this paper, we propose modelling human translation production as a hierarchy of three embedded translation processes. The proposed architecture replicates the temporal dynamics of keystroke production across sensorimotor, cognitive, and phenomenal layers. Utilizing data from the CRITT TPR-DB, the Task Segment Framework, and the HOF taxonomy, we demonstrate the temporal breakdown of the typing flow on distinct timelines within these three layers.

Empirical Translation Process Research: Past and Possible Future Perspectives

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.

The Monitor Model and its Misconceptions: A Clarification

Horizontal (automatic) and vertical (control) processes have long been reported in human translation production (e.g., Konig 1987, Lorscher 1991, Jaaskelainen 1996, de Groot 1997, Tirkkonen-Condit 2005, Macizo and Bajo 2006). The Monitor Model (Schaeffer and Carl 2013, 2015) integrates horizontal and vertical processes, assuming priming mechanisms underlie horizontal/automatic processes, while vertical/monitoring processes implement consciously accessible control mechanisms. Carl (2021a) argues that priming processes in translation are part of perception-action loops, interpretable in an embodied/enactivist framework. Carl (2022) develops a post-humanist view on translator-technology interaction facilitated by priming mechanisms which enable representationally unmediated translator-environment coupling. I substantiate these claims, arguing that translation priming results in basic, non-representational content. I update the Monitor Model with additional evidence and address an accumulation of misconceptions.