International Journal For Multidisciplinary Research

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Chatbot Song Recommender System

Author(s) Ms. N Advytha Reddy, Ms. Lahari T, Mr. Harshith Chowdary Yepuri, Mr. Jai Ganesh
Country India
Abstract The swift progress of Artificial Intelligence (AI) and Machine Learning (ML) has made it possible to create intelligent conversation agents that not only understand but also react to human feelings. In this context, the project presents the Chatbot Song Recommender System which is a smart integration of Natural Language Processing (NLP), sentiment analysis, and music recommendation algorithms. To some extent, this system even supersedes the traditional chatbots deployed in business as it is aimed at casual interaction and human-like entertainment personalized for the particular user. The IBM Tone Analyzer API is used by the chatbot to perform the analysis of the user’s emotional tone which could be joy, sadness, or anger, for instance, during the talk. The emotion detected is then used by the system to pull the relevant songs from the Last.fm API that would be in sync with the user’s mood. The development of the chatbot is done with Python, while scikit-learn and TensorFlow are among the libraries used for implementing the machine learning functionalities. This method intends to make the user experience more interactive, thereby connecting conversational AI and emotional intelligence, as well as revealing the possibilities of AI in the realm of interactive entertainment applications.
Keywords —Chatbot, Song Recommender System, Natural Language Processing (NLP), Sentiment Analysis, Emotion Detec tion, IBM Tone Analyzer API, Last.fm API, Conversational AI
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 8, Issue 1, January-February 2026
Published On 2026-02-05
DOI https://doi.org/10.36948/ijfmr.2026.v08i01.67708
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