Description
Abstract: Existing research articulates difficulties masks cause in the interpretation of emotions (e.g., Carbon, 2020). The COVID-19 pandemic is an unprecedented time in which the impact of the pandemic on individuals' emotional processing is yet to be determined. Previous work in our lab has looked at interactions between audiovisual perception, emotion recognition, and memory without the use of masks; this work and existing research provide a baseline for my current project investigating the detection of facial emotions based on auditory cues during mask wearing. The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) is a verified tool to help analyze emotional reactions in individuals that was used in conjunction with the Facial Masks and Respirators Database (FMR-DB) which displays images of individuals with different types of masks. Participants heard sentences neutral in content (e.g., "dogs are sitting by the door") spoken in either a happy, sad, or neutral tone accompanied by masked or unmasked ambiguous faces. The purpose of the present study was to see how vocal expression of emotion can change the emotions detected on faces. We expect participants to interpret the ambiguous non-masked faces in a strong emotional manner when listening to the emotionally-charged audios. We also expect participants to have greater difficulty interpreting masked faces and rating them more neutral despite the emotion of the accompanied audio. The findings for this study are influential during COVID-19 as they may help mitigate communication complications as a result of the pandemic.
Included in
Pandemic Emotion Perception
Abstract: Existing research articulates difficulties masks cause in the interpretation of emotions (e.g., Carbon, 2020). The COVID-19 pandemic is an unprecedented time in which the impact of the pandemic on individuals' emotional processing is yet to be determined. Previous work in our lab has looked at interactions between audiovisual perception, emotion recognition, and memory without the use of masks; this work and existing research provide a baseline for my current project investigating the detection of facial emotions based on auditory cues during mask wearing. The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) is a verified tool to help analyze emotional reactions in individuals that was used in conjunction with the Facial Masks and Respirators Database (FMR-DB) which displays images of individuals with different types of masks. Participants heard sentences neutral in content (e.g., "dogs are sitting by the door") spoken in either a happy, sad, or neutral tone accompanied by masked or unmasked ambiguous faces. The purpose of the present study was to see how vocal expression of emotion can change the emotions detected on faces. We expect participants to interpret the ambiguous non-masked faces in a strong emotional manner when listening to the emotionally-charged audios. We also expect participants to have greater difficulty interpreting masked faces and rating them more neutral despite the emotion of the accompanied audio. The findings for this study are influential during COVID-19 as they may help mitigate communication complications as a result of the pandemic.