AI Personalized Mantra Recommender
Meenakshy Shiju, B. J. Gouri, Raghav Mehra
IEEE International Symposium on Compound Semiconductors November 14, 2025 DOI: 10.1109/iscs69371.2025.11386063 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Prototype system paper Peer reviewed |
|---|---|
| Measures | Big Five Inventory |
| Key points | The authors propose and prototype an AI conversational agent that personalizes mantra recommendations using Big Five personality assessment and real-time emotion detection via natural language processing, voice, and optional facial recognition. They report early results indicating context-sensitive recommendations that increased user engagement and emotional resonance, and argue these findings support the potential of AI-personalized spiritual health systems. |
Abstract
Increasing levels of stress and digital fatigue underscore the need for personalized wellness interventions. Though mantra meditation has been shown to have psychological and physiological benefits, wellness platforms currently in existence are generally generic. This paper introduces an AI-powered conversational agent that suggests mantras tailored to users’ personality traits and emotional states. The platform combines the Big Five Inventory for personality assessment with real-time emotion detection using natural language processing, voice, and optional facial recognition. A hybrid recommendation system, integrating rule-based reasoning and adaptive machine learning, translates user states to mantras that induce calmness, concentration, or energy. Deployed in Python (Flask) with text and voice-based interactivity, the prototype leverages a curated Vedic mantra database annotated with desired outcomes. Early results indicate context-sensitive and successful recommendations that increase user engagement and emotional resonance, supporting the potential of AI-personalized spiritual health systems.