Year: 2025
Type: article
Abstract: In the rapidly evolving world of artificial intelligence, voice assistants have become a pivotal element of human-computer interaction. Aurora is an intelligent AI-powered voice assistant designed to deliver a personalized and interactive experience by combining emotion detection, facial recognition, chatbot integration, and mobile automation. Utilizing machine learning algorithms like LBPH for facial recognition and neural networks for emotion-based music recommendation, Aurora adapts its responses based on the user's mood and commands. The assistant is equipped with hot word detection, WhatsApp messaging, making it a versatile tool for everyday tasks. Aurora also integrates ChatGPT-like capabilities via Hugging Face, offering intelligent and context-aware conversations. Built with Python, OpenCV, MediaPipe, and Streamlit, Aurora redefines digital interaction, blending real-time vision, voice, and automation into a seamless user experience. Key Words: Voice Assistant, Emotion Detection, Facial Recognition, LBPH Algorithm, Neural Network Music Recommendation, Hotword Detection, Chatbot Integration
DOI: 10.55041/ijsrem44587
Authors: P. Deepthi, A. Likhitha
Language: English
Topic: Speech and dialogue systems
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4409465475