Communicating and reading emotion with masked faces in the Covid era: A short review of the literature

Ramdani, Céline; Ogier, Michaël; Coutrot, Antoine

doi:10.1016/j.psychres.2022.114755

Cited by 22 publications

(6 citation statements)

References 115 publications

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“…These include visual cues like facial expression or gestures that can increase the understanding of a speaker’s intent under challenging listening conditions such as in background noise ( Moradi et al, 2013 ), or convey nuances like irony or sarcasm ( Sumby and Pollack, 1954 ; Sommers et al, 2005 ; Moradi et al, 2013 ). For instance, the lack of ability of listeners to incorporate non-verbal context can contribute to miscommunication in aging, communication disorders, or under conditions like facial masking in healthcare settings ( Rankin et al, 2009 ; Ujiie et al, 2015 ; Moradi et al, 2016 ; Nuber et al, 2018 ; Ramdani et al, 2022 ). In the case of animal signalers, visual displays or olfactory cues in combination with vocalizations may likewise clarify a signal relative to background noise or transform its meaning (e.g., Smith and Evans, 2008 ; Ronald et al, 2017 , 2020 ; Caldart et al, 2022 ).…”

Section: Introductionmentioning

confidence: 99%

Listening to your partner: serotonin increases male responsiveness to female vocal signals in mice

Hood,

Hurley

2024

Front. Hum. Neurosci.

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The context surrounding vocal communication can have a strong influence on how vocal signals are perceived. The serotonergic system is well-positioned for modulating the perception of communication signals according to context, because serotonergic neurons are responsive to social context, influence social behavior, and innervate auditory regions. Animals like lab mice can be excellent models for exploring how serotonin affects the primary neural systems involved in vocal perception, including within central auditory regions like the inferior colliculus (IC). Within the IC, serotonergic activity reflects not only the presence of a conspecific, but also the valence of a given social interaction. To assess whether serotonin can influence the perception of vocal signals in male mice, we manipulated serotonin systemically with an injection of its precursor 5-HTP, and locally in the IC with an infusion of fenfluramine, a serotonin reuptake blocker. Mice then participated in a behavioral assay in which males suppress their ultrasonic vocalizations (USVs) in response to the playback of female broadband vocalizations (BBVs), used in defensive aggression by females when interacting with males. Both 5-HTP and fenfluramine increased the suppression of USVs during BBV playback relative to controls. 5-HTP additionally decreased the baseline production of a specific type of USV and male investigation, but neither drug treatment strongly affected male digging or grooming. These findings show that serotonin modifies behavioral responses to vocal signals in mice, in part by acting in auditory brain regions, and suggest that mouse vocal behavior can serve as a useful model for exploring the mechanisms of context in human communication.

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Section: Introductionmentioning

confidence: 99%

Listening to your partner: serotonin increases male responsiveness to female vocal signals in mice

Hood,

Hurley

2024

Front. Hum. Neurosci.

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“…Masks also bias social judgments of trustworthiness, in some cases negatively (Biermann et al, 2021;Marini et al, 2021;Bylianto and Chan, 2023) and in others positively (Cartaud et al, 2020). Perhaps most strikingly, humans have been found to be significantly impaired at recognizing all six basic emotions when faces are covered with face masks (e.g., Carbon, 2020;Noyes et al, 2021;Pazhoohi et al, 2021;Aguillon-Hernandez et al, 2022;Blazhenkova et al, 2022;Ramachandra and Longacre, 2022;Ramdani et al, 2022;Rinck et al, 2022;Wong and Estudillo, 2022;McCrackin et al, 2022a;Proverbio et al, 2023 for a review). This general emotion recognition detriment varies with individual emotions, such that the largest impairment is typically reported for disgust (e.g., Carbon, 2020;Rinck et al, 2022;Wong and Estudillo, 2022;McCrackin et al, 2022a) and the smallest for fear (e.g., Carbon, 2020;McCrackin et al, 2022a).…”

Section: Introductionmentioning

confidence: 99%

Improving masked communication: the case for transparent masks

McCrackin,

Ristic

2024

Front. Commun.

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Clear and compassionate communication is tantamount to quality of care and patient wellbeing. Yet, much of communication in healthcare occurs with lower faces visually hidden behind opaque face masks. Visual occlusion of the face by masks impairs both verbal and nonverbal communication, including recognition of basic emotions, perceptions of trustworthiness, emotional understanding, and empathic responding. This piece presents a brief overview of the new COVID-19 inspired literature which shows that visual face occlusion creates significant communication barriers which can be reduced by wearing transparent instead of opaque masks.

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“…As a result, they may impair the observer’s ability to accurately identify the emotions conveyed by a person’s facial expressions [ 8 ]. A survey has shown that adults’ identification accuracy dropped when asked to identify faces with their mouths covered [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

Masked Face Emotion Recognition Based on Facial Landmarks and Deep Learning Approaches for Visually Impaired People

Mukhiddinov

Djuraev

Akhmedov

et al. 2023

Sensors

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Current artificial intelligence systems for determining a person’s emotions rely heavily on lip and mouth movement and other facial features such as eyebrows, eyes, and the forehead. Furthermore, low-light images are typically classified incorrectly because of the dark region around the eyes and eyebrows. In this work, we propose a facial emotion recognition method for masked facial images using low-light image enhancement and feature analysis of the upper features of the face with a convolutional neural network. The proposed approach employs the AffectNet image dataset, which includes eight types of facial expressions and 420,299 images. Initially, the facial input image’s lower parts are covered behind a synthetic mask. Boundary and regional representation methods are used to indicate the head and upper features of the face. Secondly, we effectively adopt a facial landmark detection method-based feature extraction strategy using the partially covered masked face’s features. Finally, the features, the coordinates of the landmarks that have been identified, and the histograms of the oriented gradients are then incorporated into the classification procedure using a convolutional neural network. An experimental evaluation shows that the proposed method surpasses others by achieving an accuracy of 69.3% on the AffectNet dataset.

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Communicating and reading emotion with masked faces in the Covid era: A short review of the literature

Cited by 22 publications

References 115 publications

Listening to your partner: serotonin increases male responsiveness to female vocal signals in mice

Listening to your partner: serotonin increases male responsiveness to female vocal signals in mice

Improving masked communication: the case for transparent masks

Masked Face Emotion Recognition Based on Facial Landmarks and Deep Learning Approaches for Visually Impaired People

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