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Disentangling cognitive and emotional load in interpreting

Multimodal evidence from physiological, acoustic, and self-report measures

ORCiD logo with link | Hacettepe University
ORCiD logo with link | Bilkent University
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Abstract
This study employs a multimodal approach to investigate how emotional and cognitive load differentially impact interpreter stress. Twenty student interpreters consecutively interpreted four Turkish-to-English mental healthcare narratives of varying emotionality and difficulty, constructed using a 2×2 factorial design. Stress responses were measured using galvanic skin response (GSR), voice parameters (pitch and voice intensity), and self-report scales (PANAS, STAI, and NASA-TLX). Stimuli were normed for emotional valence and linguistic complexity using readability indices, expert ratings, and natural language processing (NLP) tools. Results showed that primarily cognitive load drove GSR arousal, particularly during later interpreting stages, whereas emotional load was reflected in pitch and self-reported negative affect. A pitch convergence between speaker and interpreter also emerged. None of the stress indicators predicted interpreting accuracy, suggesting a possible role for individual coping strategies.
Article outline
  • 1.Introduction
  • 2.Methods
    • 2.1Participants
    • 2.2Stimuli
    • 2.3Norming
      • 2.3.1Text-based norming
      • 2.3.2Human ratings
      • 2.3.3NLP-based profiling
    • 2.4Procedure
  • 3.Results
    • 3.1Data analysis approach
      • 3.1.1Skin conductance
      • 3.1.2Auditory output
      • 3.1.3Statistical models
    • 3.2Self-report measures
    • 3.3Skin conductance
      • 3.3.1Difference between the phases
      • 3.3.2Time course of skin conductance
    • 3.4Voice parameters
      • 3.4.1Voice intensity
      • 3.4.2Mean fundamental frequency
      • 3.4.3Fundamental frequency variation
    • 3.5Accuracy and source-target synchronisation
  • 4.Discussion
  • 5.Conclusion
  • References
References (93)
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