International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Song Recommender Chatbot

Author(s) Mr. Nikhil Jain, Mr. Shivam Pachauri, Mukesh Kumar Jha
Country India
Abstract This project presents the design and development of a Chatbot-based Song Recommender System that tailors music recommendations to users based on their interests and preferences.
The system leverages natural language processing (NLP) techniques to interpret user inputs and generate personalized music suggestions. By continuously learning from user interactions, the chatbot refines its recommendations over time, ensuring a more accurate and satisfying user experience.
To enhance the system's effectiveness, we propose integrating sensors in future iterations, allowing the chatbot to analyze environmental and physiological data. These sensors could track factors such as heart rate, location, or even ambient noise levels, providing a more holistic understanding of the user's context and mood. This integration aims to create a more immersive and adaptive music recommendation experience, further aligning with the user's real-time emotional and situational needs.
The proposed system has significant potential in various applications, from personalized entertainment to therapeutic settings where music plays a crucial role. This project explores the underlying technologies, system architecture, and the potential impact of sensor integration on the future of personalized music recommendation systems.
Keywords Song Recommender Chatbot
Field Arts > Movies / Music / TV
Published In Volume 8, Issue 1, January-February 2026
Published On 2026-01-15
DOI https://doi.org/10.36948/ijfmr.2026.v08i01.66749
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E-ISSN 2582-2160
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