Quantifying facial expression intensity and signal use in deaf signers

Helen Rodger , Junpeng Lao (1) , Chloé Stoll (2) , Anne-Raphaëlle Richoz (2) , Olivier Pascalis (2) , Matthew Dye , Roberto Caldara (3)

1 Département de Psychologie
2 LPNC - Laboratoire de Psychologie et NeuroCognition
3 UNIFR - Université de Fribourg = University of Fribourg

We live in a world surrounded by rich dynamic multisensory signals. Hearing individuals rapidly and effectively integrate multimodal signals to decode biologically relevant facial expressions of emotion. Yet, it remains unclear how facial expressions are decoded in deaf adults in the absence of an auditory sensory channel. We thus compared early and profoundly deaf signers (n = 46) with hearing non-signers (n = 48) on a psychophysical task designed to quantify their recognition performance for the six basic facial expressions of emotion. Using neutral-to-expression image morphs and noise-to-full signal images, we quantified the intensity and signal levels required by observers to achieve expression recognition. Using Bayesian modelling, we found that deaf observers require more signal and intensity to recognize disgust, while reaching comparable performance for the remaining expressions. Our results provide a robust benchmark for the intensity and signal use in deafness and

Domaines: Psychologie et comportements

Helen Rodger, Junpeng Lao, Chloé Stoll, Anne-Raphaëlle Richoz, Olivier Pascalis, et al.. Quantifying facial expression intensity and signal use in deaf signers. Journal of Deaf Studies and Deaf Education, 2019, 24 (4), pp.346-355. ⟨10.1093/deafed/enz023⟩. ⟨hal-02567187v2⟩