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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
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Published Paper Details:
Paper Title
MoodTune: AI-Based Emotion Recognition and Music Recommendation System
Authors
Prof Mali Amol, Atharv Madane, Jay Patole, Pratiksha Ankushrao, Sujit Gayke
Keywords
Emotion Detection, Deep Learning, Music Recommendation, Spotify API, YouTube API, Artificial Intelligence, Human-Computer Interaction.
Abstract
In the modern digital era, emotional intelligence in technology has become a vital component of personalized user experiences. MoodTune is an AI-based system that detects users' emotions in real-time using facial expressions and voice tone and automatically recommends suitable music through Spotify and YouTube integration. The system employs Deep Learning models for emotion detection and Natural Language Processing (NLP) for voice-based mood analysis. It integrates Spotify and YouTube APIs to generate unlimited mood-based playlists, offering a seamless and adaptive entertainment experience. The project demonstrates the use of computer vision, deep learning, and cloud API integration to enhance human-computer interaction through emotion-aware multimedia recommendations.
IJCRT's Publication Details
Unique Identification Number - IJCRT2512009
Paper ID - 297934
Page Number(s) - a59-a63
Pubished in - Volume 13 | Issue 12 | December 2025
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Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
Prof Mali Amol, Atharv Madane, Jay Patole, Pratiksha Ankushrao, Sujit Gayke, "MoodTune: AI-Based Emotion Recognition and Music Recommendation System", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.13, Issue 12, pp.a59-a63, December 2025, Available at :http://www.ijcrt.org/papers/IJCRT2512009.pdf
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Volume 13 | Issue 12
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Submit Manuscript Online Impact Factor: 7.97 Review Results : Within 02-03 Days Paper Publication : Within 02-03 Days
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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