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@article{182182,
        author = {Daivashala Deshmukh and Vedika Hatolkar and Mohini Ahale and Shrutika Jarwal},
        title = {MoodSense: A Survey on AI-Based Web Applications for Mental Well-Being and Emotional Analysis},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {2},
        pages = {1149-1154},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=182182},
        abstract = {Mental well-being is a critical component of overall health, yet many individuals face barriers in recognizing or addressing emotional distress. MoodSense is an AI-based web application designed to provide real-time emotional analysis using speech and text inputs. Leveraging Natural Language Processing (NLP) and Speech Emotion Recognition (SER), the system detects a spectrum of emotional states, including happiness, sadness, stress, and anxiety. This paper presents the architecture, methodologies, and outcomes of MoodSense, emphasizing its potential as a non-invasive, scalable, and user-centric tool for emotional awareness and mental health support. Unlike traditional tools, MoodSense offers a personalized and accessible platform suitable for students, working professionals, and general users, helping bridge gaps in mental health care through technology.},
        keywords = {Mental Wellbeing, Emotion},
        month = {July},
        }