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@article{179048,
        author = {Abhay Kumar and Anuj Kumar Singh and Deepak Maurya and Kiran Singh},
        title = {Real-Time Emotional Monitoring Using Speech  Emotion Recognition for Mental Health Support},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {5294-5300},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=179048},
        abstract = {In the last few years, mental health has come to prominence as a very important issue of concern. It's of great importance to provide early-stage identification as well as continuous monitoring for mental issues. This work presents a method for Speech Emotion Recognition (SER) which aims to improve mental health evaluation by classification of emotions in speech automatically. The system classifies emotions automatically into four categories: happy, sad, neutral, and angry. Besides that, the stopping of the audio recording is done remotely to collect relevant attributes such as pitch, tone, and energy of the audio signals. Based on the classification, insight into the psychological well- being of the person can be attained which can be used to aid routine assessment and prompt mental health treatments. The proposed model is trained and evaluated using an open-access dataset containing emotionally-laden pictures and shows great results in detecting heart- rending emotion in real-time applications. This is an attempt to develop an unobtrusive device aimed at improving the care of patients and monitoring their mental health and enabling advanced psychological care to be offered.},
        keywords = {Speech Emotion Recognition (SER), Mental Health Monitoring, Real-Time Emotion Detection, Healthcare Technology},
        month = {May},
        }