The Development of A Mobile Music Streaming Application Using Machine Learning

• Published in: 6th International Seminar on Research of Information Technology and Intelligent Systems, ISRITI 2023 - Proceeding
• Main Author: Foo K.Q.; Jalil A.; Aziz A.A.; Kolandaisamy R.; Subaramaniam K.
• Format: Conference paper
• Language: English
• Published: Institute of Electrical and Electronics Engineers Inc. 2023
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85190065340&doi=10.1109%2fISRITI60336.2023.10467814&partnerID=40&md5=1ba6c6fce6a31c609ea83d1ba81359e1

Music is an important part in human daily lives. However, it might be difficult for people to choose which type of music to listen to from a vast array of available selections. Furthermore, the people are unable to get comfort by just listening to any kind of songs as it depends on the mood. Even worse, if the songs could not comfort them, they might be depressed easily. Therefore, the main objective of this study is to develop a mobile music streaming application that can track mood based on the song played by the user using machine learning approach to recommend next suitable song. The application is designed to use Spotify library to connect it to Spotify API to get the data of the songs played by the user. The analysis of the audio features in the application may lead to the understanding of the current emotional or mental state of the user. Thus, this application is proposed to help music listeners to release their tension by suggesting the next suitable song and able to recommend suitable activities for them to relax as well. © 2023 IEEE.