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

2025-07-16

AI Summary

This study investigates the dynamic interplay among affect, cognition, and automated behavior during translation and its underlying psychological architecture. To this end, we propose the Behavior-based Translation Style Space (BTSS)—the first hierarchical computational framework integrating temporal features of affective, cognitive, and behavioral processes. Leveraging synchronized eye-tracking and keystroke-logging data, BTSS employs a multi-level embedded modeling approach to quantify cognitive load, affective fluctuation, and behavioral automation, enabling their dynamic co-simulation. Unlike prior models that treat these dimensions separately, BTSS unifies them within a single, computationally tractable, and psychologically interpretable framework. It thus advances process-oriented translation research by significantly improving both modeling fidelity and theoretical explanatory power regarding the internal mechanisms of translation.

Technology Category

• Cognitive Modeling & Cognitive Systems: Adaptive Behavior
• Natural Language Processing: Sentiment Analysis, Stylistic Analysis, and Argument Mining
• Multiagent Systems: Agent-Based Simulation and Emergent Behavior

Application Category

• User Modeling, Personalization and Recommendation: Studies of user behavior, including longitudinal effects of personalized systems
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Web Mining and Content Analysis: Models for Web evolution

Abstract

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.

Problem

• Model behavioral translation patterns using hierarchical processing layers
• Link eye and finger movements to cognitive and affective states
• Simulate human translation dynamics via computational agent

Innovation

• Hierarchical Behavioural Translation Style Space
• Keystroke and gaze data analysis
• Computational agent simulates translation dynamics