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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM61136

Mind Melodies: Your Personal Emotional Soundtrack

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM61136

Volume:

10 |

4 |

April 2026

Pages:

Publication Frequency:

Monthly (12 issues per year)

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Not assigned

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

BVN

Bhukya Vishal Naik

NS

Nangunuri Srinadh

SS

Shweta Sharma

SAJ

S. Asha Jyothi

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Abstract

The system Mind Melodies: Your Personal Emotional Soundtrack introduces an AI-based approach to create personalized emotional responses through real- time facial expression recognition. Traditional music recommendation systems do not consider the user’s emotional state, leading to less meaningful interactions. To address this, the project integrates emotion detection, text sentiment mapping, and curated music selection into a unified framework. The methodology uses a deep-learning facial emotion recognition model to classify the user’s mood and generates a corresponding quote, emoji, and song selection. The system processes webcam input, extracts facial features, and maps the detected emotion to a predefined emotional database. Through this multimodal response, the system enhances emotional engagement and offers a supportive, mood-based interaction. Experimental results demonstrate that combining real-time vision analysis with emotion-linked music selection provides an effective and interactive experience. The project highlights the potential of AI-driven emotional understanding for personalized well-being applications.

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Cite This Article

Bhukya Vishal Naik, Nangunuri Srinadh, Shweta Sharma, S. Asha Jyothi, "Mind Melodies: Your Personal Emotional Soundtrack," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 4, April 2026.

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Publication Date

4/24/2026

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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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