Designing Emotion-Aware Systems for Human–Computer Interaction in the Web Age

Abstract

The advent of new digital technologies and the introduction of online services have made Human-Computer
Interaction (HCI) part and parcel of daily life. The traditional models of HCI concentrate on task-based interaction
metrics of usability, often neglecting underlying emotional states. This paper tries to fill this gap by proposing a
comprehensive approach for designing systems that recognize and respond to users’ emotions in the contemporary
web era. The plan is to build systems that automatically and dynamically recognize, analyze, and respond to human
emotions through facial expression, voice, and sentiment analysis of text. We employed affective computing, deep
learning, and real-time emotion recognition algorithms within a single framework which is aimed to improve the
overall user experience and participation in the system. The proposed system, demonstrably, achieves more than 88%
accuracy in emotion detection along with improved user satisfaction measures in adaptive interfaces. The system
outperformed baseline emotion detection systems in relation to task completion and emotional engagement. The
results highlight the need to integrate emotional intelligence and sensitivity on interactivity designs to facilitate more
human-like and compassion-driven interactions. This work augments the literature on ‘Affective Human Computer
Interaction’, bringing forth new insights about guiding future research, development, and deployment in emotionsensitive
system designs.v