UR-112 Monarch: A Privacy-focused NLP Model for Emotional Pattern Detection

Introducing: Monarch — a privacy-focused deep learning model that interprets emotional patterns in text. Monarch is trained on large, lexicon-based datasets and uses fine-tuned NLP models (BERT) to identify patterns associated with sadness, worry, anger, and distress. It runs entirely offline with no data collection, making it ideal for private use. Monarch evaluates text and returns clear, readable probability scores across emotional categories, giving users insight into emotional trends. Monarch is interpretive, not diagnostic, displaying results based on scientifically backed linguistic patterns. Its potential use in schools could help flag early signs of distress, giving educators a chance to support those in need. Monarch is also suitable for research in linguistics, mental health, and ethical AI implementations.