Aurora – Revolutionizing Human-AI Interaction – “Hey Luna”

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

Authors

Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2025-04-15
DOI
https://doi.org/10.55041/ijsrem44587
Primary Topic
Economic and Technological Developments in Russia
Type
article
Field-Weighted Citation Impact
0.00
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article

Aurora – Revolutionizing Human-AI Interaction – “Hey Luna”

P. Deepthi, A. Likhitha
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Economic and Technological Developments in Russia
article

Aurora – Revolutionizing Human-AI Interaction – “Hey Luna”

P. Deepthi, A. Likhitha
article en

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

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 09(04)
Openalex Percentile: Top 85%
Economic and Technological Developments in Russia
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