Dr. Eslam Amer
Eng. Mahmoud Heidar
Our project aims to develop a smart AI chatbot that can assess user behavior and provide personalized replies to individuals facing psychological issues, including autism, PPD, and communication difficulties to practice their communication skills. By incorporating the learning agent model and leveraging natural language generation techniques such as GPT-3, our chatbot enhances natural language processing capabilities and provides corrections in addition to answering user queries. The integration of a hidden Markov model enables analysis of user behavior for generating tailored responses. By mimicking human emotions and reactions during conversations, our system aims to enhance the user experience and provide a more empathetic interaction. Additionally, for user well-being, if negative thoughts arise or the case is severe, the session automatically ends and users are directed to chat with the psychiatrist, with their consent ensuring confidentiality. Overall, our goal is to create an intelligent AI system that supports individuals with communication issues, promoting their overall psychological well-being.
- Develop an AI chatbot for personalized solutions in autism, PPD, and communication issues.
- Utilize NLP technologies like GPT-3 for accurate and contextually appropriate responses.
- Incorporate a hidden Markov model for analyzing user behavior and generating tailored responses.
- Enhance user experience by mimicking human emotions and reactions during conversations.
- Improve overall psychological well-being through personalized assistance and solutions.
- Ensure user-friendliness for different age groups (children, teens, adults, seniors).
- Continuously update and improve the system based on user feedback and research.
- Strive for accuracy and reliability in understanding and responding to user queries.
- Provide professional help if needed.
- Ethically handle user data, prioritizing privacy and security.
- Intelligent chatbot provides tailored responses based on user actions.
- Machine learning algorithms are used to analyze user activities and deliver relevant responses.
- Equipped with a natural language processing (NLP) engine for comprehending user input and generating appropriate responses (GPT-3).
- Contains a database of user data, previous chat sessions and personalized dataset containing the regular sequences of emotions for each user.
- Learns from past interactions to improve responses over time.
- Accessible 24/7 and compatible with various platforms (computers, mobile devices).
- Adaptable and expandable to accommodate future growth and system integration.
- Strong security & privacy features to ensure the protection of users’ information.
Documents and Presentations
You will find here the documents and presentation for our proposal.
You will find here the documents and presentation for our SRS.
You will find here the documents and presentation for our SDD.
You will find here the documents and presentation for our Thesis
International Science and Engineering Innovations Competition (ISEIC’2023)
Our team achieved a significant milestone by qualifying for the final stage of the ISEAC competition for our project, standing out among the 769 teams that applied and securing our place among the top 150 qualified teams.