Mirror Ritual: An Affective Interface for Emotional Self-Reflection
This addresses the problem of emotional regulation for individuals through an incremental interface that builds on existing emotion theories and AI models.
The paper tackled the problem of fostering emotional self-reflection by introducing Mirror Ritual, an affective interface that uses facial expression recognition to generate personalized poetry, resulting in participants engaging with the interface and developing unique interpretations of the poetry.
This paper introduces a new form of real-time affective interface that engages the user in a process of conceptualisation of their emotional state. Inspired by Barrett's Theory of Constructed Emotion, `Mirror Ritual' aims to expand upon the user's accessible emotion concepts, and to ultimately provoke emotional reflection and regulation. The interface uses classified emotions -- obtained through facial expression recognition -- as a basis for dynamically generating poetry. The perceived emotion is used to seed a poetry generation system based on OpenAI's GPT-2 model, fine-tuned on a specially curated corpus. We evaluate the device's ability to foster a personalised, meaningful experience for individual users over a sustained period. A qualitative analysis revealed that participants were able to affectively engage with the mirror, with each participant developing a unique interpretation of its poetry in the context of their own emotional landscape.