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@article{175549,
        author = {S. V. Rama Rao and M. Sankar and L. Rishi and M. Vinay Kumar and K. Guna Veeranna and Md. Alfan Babu},
        title = {Multi-Modal Biometric Access System Using Face,  Emotion, and Voice Recognition},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {3058-3063},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=175549},
        abstract = {The Real-Time Emotion-Based Access Control System has a multi-level authentication system with secure access based on facial recognition, voice, and emotional authentication. It records user’s facial photos, voice samples, and verbal passwords during registration through the use of Automatic Speech Recognition (ASR) technology driven by Whisper, FaceNet for facial recognition, Mel-Frequency Cepstral Coefficients (MFCC) in combination with Support Vector Machine (SVM) for voice recognition, and Multi-task Cascaded Convolutional Networks (MTCNN) for facial detection. Further, the system stores the user's average facial emotion for better verification. On authentication, it verifies facial identity, voice identity, verbal password, and emotional match, hence enhancing security controls. Through AI-driven authentication and emotion-based verification, the system enhances access control and reduces unauthorized entries.},
        keywords = {Automatic Speech Recognition, Emotion Analysis, Facial Recognition, Mel-Frequency Cepstral Coefficients, Real-Time Authentication, Voice Recognition.},
        month = {April},
        }