Temporal Dynamics of Emotion and Cognition in Human Translation: Integrating the Task Segment Framework and the HOF Taxonomy

TL;DR

This paper presents a generative model of the human translating mind, linking behavioral data to three concurrent mental processing layers—automatic, reflective, and emotional—using empirical keystroke and gaze data.

Contribution

It introduces a novel generative model grounded in empirical translation process data, integrating behavioral signals with cognitive and emotional processing layers.

Findings

Behavioral data reveals three concurrent processing layers in translation.

Keystroke and gaze patterns correlate with different mental states.

The model connects empirical data with theoretical frameworks in translation studies.

Abstract

The article develops a generative model of the human translating mind, grounded in empirical translation process data. It posits that three embedded processing layers unfold concurrently in the human mind, and their traces are detectable in behavioral data: sequences of routinized/automated processes are observable in fluent translation production, cognitive/reflective thoughts lead to longer keystroke pauses, while affective/emotional states may be identified through characteristic typing and gazing patterns. Utilizing data from the CRITT Translation Process Research Database (TPR-DB), the article illustrates how the temporal structure of keystroke and gaze data can be related to the three assumed hidden mental processing strata. The article relates this embedded generative model to various theoretical frameworks, dual-process theories and Robinson's (2023) ideosomatic theory of translation, opening exciting new theoretical horizons for Cognitive Translation Studies, grounded in empirical data and evaluation.