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Design and Development of an Alexa-Based Music Recommendation Bot Using Machine Learning

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Volume-10 | Innovations in Computer Science and Applications

Last date : 28-Mar-2026

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Design and Development of an Alexa-Based Music Recommendation Bot Using Machine Learning


Akanksha Shirbhate



Akanksha Shirbhate "Design and Development of an Alexa-Based Music Recommendation Bot Using Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Innovations in Computer Science and Applications, April 2026, pp.21-29, URL: https://www.ijtsrd.com/papers/ijtsrd101403.pdf

Voice-controlled assistants have changed how we use systems. This research is about designing and building a music bot for Alexa that uses machine learning to make music suggestions and playback better with voice commands. The system combines Amazon Alexa with machine learning to understand what users like, process voice inputs and give music suggestions. The proposed model uses natural language processing to understand what users say and get the music commands. A machine learning module analyzes what users listen to, their behavior and other details to suggest songs they might like. The system connects to music streaming services in the cloud. Uses APIs to get and play music right away. The system has four parts: * a voice input interface * a machine learning recommendation engine * a cloud processing unit * a music streaming integration module. The recommendation engine uses methods, like filtering and content-based filtering to get better at suggesting music over time. Experimental results show that the system understands voice commands and gives music suggestions making users happier and more efficient. The Alexa-based music bot works well with voice commands. Provides good music suggestions. The system makes music playback better with voice commands and machine learning.

Amazon Alexa, Machine Learning, Music Recommendation System, Natural Language Processing, Voice Assistant, Collaborative Filtering, Speech Recognition.


IJTSRD101403
Special Issue | Innovations in Computer Science and Applications, April 2026
21-29
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

International Journal of Trend in Scientific Research and Development - IJTSRD having online ISSN 2456-6470. IJTSRD is a leading Open Access, Peer-Reviewed International Journal which provides rapid publication of your research articles and aims to promote the theory and practice along with knowledge sharing between researchers, developers, engineers, students, and practitioners working in and around the world in many areas like Sciences, Technology, Innovation, Engineering, Agriculture, Management and many more and it is recommended by all Universities, review articles and short communications in all subjects. IJTSRD running an International Journal who are proving quality publication of peer reviewed and refereed international journals from diverse fields that emphasizes new research, development and their applications. IJTSRD provides an online access to exchange your research work, technical notes & surveying results among professionals throughout the world in e-journals. IJTSRD is a fastest growing and dynamic professional organization. The aim of this organization is to provide access not only to world class research resources, but through its professionals aim to bring in a significant transformation in the real of open access journals and online publishing.

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