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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM44587

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

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM44587

Volume:

9 |

4 |

Apr 2025

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM44587

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

PD

P. Deepthi1

AL

A. Likhitha2

AD

A. Dhanush3

KY

K. Yeswanth4

GHVR

G. Hasha Vardan Reddy5

MPM

Ms. P.V.S. Manisha6

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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.

KEYWORDS

Voice Assistant Emotion Detection Facial Recognition LBPH Algorithm Neural Network Music Recommendation Hotword Detection Chatbot Integration

Cite This Article

P. Deepthi1, A. Likhitha2, A. Dhanush3, K. Yeswanth4, G. Hasha Vardan Reddy5, Ms. P.V.S. Manisha6, "Aurora – Revolutionizing Human-AI Interaction – “Hey Luna”," International Journal of Scientific Research in Engineering and Management, vol. 9, no. 4, Apr 2025. https://doi.org/10.55041/IJSREM44587

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Publication Date

4/14/2025

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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