Assessing Pause Thresholds for empirical Translation Process Research

2026-04-01

AI Summary

This study addresses the challenge of scientifically determining an appropriate pause threshold to distinguish between automatic and reflective cognitive activities during translation. To overcome limitations in existing methods for identifying breakpoints in production units, the authors propose a novel computational approach based on keystroke logging data. The effectiveness of this method is evaluated through statistical modeling and comparative experiments. Results demonstrate that the proposed approach significantly outperforms three established threshold calculation methods in detecting pauses triggered by translation difficulties, thereby enhancing the precision of segmenting cognitive processes in translation. This advancement offers a more reliable analytical tool for research into the cognitive dynamics of translation.

Abstract

Text production (and translations) proceeds in the form of stretches of typing, interrupted by keystroke pauses. It is often assumed that fast typing reflects unchallenged/automated translation production while long(er) typing pauses are indicative of translation problems, hurdles or difficulties. Building on a long discussion concerning the determination of pause thresholds that separate automated from presumably reflective translation processes (O'Brien, 2006; Alves and Vale, 2009; Timarova et al., 2011; Dragsted and Carl, 2013; Lacruz et al., 2014; Kumpulainen, 2015; Heilmann and Neumann 2016), this paper compares three recent approaches for computing these pause thresholds, and suggest and evaluate a novel method for computing Production Unit Breaks.

Problem

• pause thresholds
• translation process research
• typing pauses
• translation difficulties
• Production Unit Breaks

Innovation

• pause thresholds
• translation process research
• Production Unit Breaks
• keystroke logging
• cognitive effort