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[1N4-GS-10-05] Exploring Objective Metrics for Measuring Concentration and Interest in Children's Online Communication using AI-Assisted Facial Expression Analysis
Keywords:Facial Expression Recognition, Speech-Language-Hearing Therapy, Online Communication
Speech-language-hearing therapists sometimes provide therapy for children with speech and hearing difficulties to improve their communication skills. However, there can be problems such as the need to attend therapy sessions at an institution.
The aim of this study is to explore an objective metrics that reflects the degree of concentration and interest during online communication, using videos.
A total of 57 videos during online communication obtained from 19 children were input to a facial expression recognition AI model, and the proportion of emotions in each video was output. Additionally, we conducted a survey to assess the children's concentration and interest levels during communication. We compared the results of the AI model analysis and the results of the survey.
The results showed a weak to moderate correlation between the proportion of time recognized as "Happiness" by the AI model and the proportion of time when faces were not detected, with the children's degree of concentration and interest. It is suggested that these outputs from the AI model can serve as objective metrics for measuring the degree of concentration and interest during online communication for children.
The aim of this study is to explore an objective metrics that reflects the degree of concentration and interest during online communication, using videos.
A total of 57 videos during online communication obtained from 19 children were input to a facial expression recognition AI model, and the proportion of emotions in each video was output. Additionally, we conducted a survey to assess the children's concentration and interest levels during communication. We compared the results of the AI model analysis and the results of the survey.
The results showed a weak to moderate correlation between the proportion of time recognized as "Happiness" by the AI model and the proportion of time when faces were not detected, with the children's degree of concentration and interest. It is suggested that these outputs from the AI model can serve as objective metrics for measuring the degree of concentration and interest during online communication for children.
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