AI – BASED AUTOMATIC MUSIC RECOMMENDATION FOR WHATSAPP STATUS USING MULTIMODAL VIDEO UNDERSTANDING

Registration ID: IJNRD_327296

Published ID: IJNRD2607315

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Manisha Wadkar, Ravindra Kamble

Index Terms—Artificial Intelligence, Multimodal Learning, Vision-Language Model, Large Language Model, Music Recommendation, WhatsApp Status, Sentiment Analysis.

Objective: The proliferation of ephemeral video sharing on platforms like WhatsApp has created a significant demand for automated content enhancement tools. Users frequently struggle to select background audio that semantically and emotionally aligns with visual content, leading to 'decision fatigue.' This research aims to develop a privacy-centric, multimodal Artificial Intelligence system capable of analyzing video content to recommend contextually appropriate music without relying on user historical data. Methods: The proposed architecture integrates a Vision-Language Model (VLM), specifically Moondream 2, for efficient visual scene understanding, coupled with a Large Language Model (LLM), Google Gemini, for semantic reasoning and 'vibe' generation. The pipeline extracts keyframes from user-uploaded videos, generates textual descriptions of the visual scene, translates these descriptions into musical taxonomy tags, and retrieves tracks via the Spotify Search API. Results: Experimental evaluation across diverse video categories—including travel, celebratory events, and emotional monologues—demonstrated that the system successfully identifies complex emotional cues that text-only metadata fails to capture. The integration of VLM allows for high-fidelity scene interpretation, resulting in a relevant song recommendation rate significantly higher than baseline keyword matching. Conclusion: The system provides a robust solution for automating music selection, enhancing user experience through context-aware multimodal analysis while preserving user privacy by operating on a stateless architecture.

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Manisha Wadkar & Ravindra Kamble (July-2026). AI – BASED AUTOMATIC MUSIC RECOMMENDATION FOR WHATSAPP STATUS USING MULTIMODAL VIDEO UNDERSTANDING. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 11(7), d133-d139. https://ijnrd.org/papers/IJNRD2607315.pdf

Volume 11 Issue 7, July-2026

Pages : d133-d139

Paper Reg. ID: IJNRD_327296

Published Paper Id: IJNRD2607315

Research Area: Other area not in list

Author Type: Indian Author

Country: Kolhapur, Maharashtra, India

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