A Deep Learning Based Facial Emotion Recognition System Including Chat Bot

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@article{1716902,
      author = {Divesh Singh, Harsh Raut, Dr. Sanjay Pachauri},
      title = {A Deep Learning Based Facial Emotion Recognition System Including Chat Bot},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {10},
      pages = {3506-3511},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1716902.pdf},
      abstract = {Understanding human emotions through facial expressions is an important aspect of improving interaction between humans and machines. This research presents a deep learning–based system for facial emotion recognition integrated with a chatbot to provide intelligent and adaptive responses. The proposed model uses Convolutional Neural Networks (CNN) to detect and classify facial expressions such as happiness, sadness, anger, surprise, fear, and neutral state from images or real-time video streams. In addition to emotion detection, the system incorporates a chatbot that analyzes the identified emotional state and generates appropriate responses using natural language processing techniques. This integration allows the system to interact with users in a more personalized and empathetic manner. The model is trained and tested on standard datasets to ensure accuracy and reliability under different conditions such as lighting variations and facial orientations. The developed system is capable of real-time performance and can be applied in various domains including mental health support, virtual assistants, customer service, and educational platforms. By combining emotion recognition with conversational capabilities, the proposed approach enhances user experience and demonstrates the effectiveness of intelligent human– computer interaction systems.},
      keywords = {Facial Emotion Recognition, Deep Learning, Convolutional Neural Network (CNN), Chatbot, Natural 
Language Processing (NLP), Human–Computer Interaction, Real-Time Emotion Detection, Artificial Intelligence, Image Processing, Emotion Classification I.},
      month = {April},
      doi = {https://doi.org/10.64388/IREV9I10-1716902}
  }