Song Recommendation Application Using Speech Emotion Recognition

Budi Setiawan, Eko and Dzulfiqar, Al Ghani Iqbal (2021) Song Recommendation Application Using Speech Emotion Recognition. International Journal on Informatics for Development, 10 (1). pp. 15-22. ISSN 2549-7448

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Official URL: http://ejournal.uin-suka.ac.id/saintek/ijid/articl...

Abstract

This research was conducted to facilitate the interaction between radio broadcasters and radio listeners during the song request process. The application produced in this study uses speech emotion recognition technology based on a person's mood, obtained from the spoken voice. This technology can change the voice into one of the mood categories. The K-Nearest Neighbor method is used to get recommendations for recommended song titles by looking for the closeness of the value between the listener's mood and the available song playlists. Based on tests conducted on broadcasters and radio listeners, this study has produced a song request application by recommending song titles according to the listener's mood, requesting songs with text messages, searching songs, and seeing song requests and song details that have been requested. Functional testing that has been carried out has received a value of 100 because all test components have succeeded as expected

Item Type: Article
Subjects: Jurnal Online
Divisions: Universitas Komputer Indonesia > Fakultas Teknik dan Ilmu Komputer > Teknik Informatika (S1)
Depositing User: EKO BUDI SETIAWAN
Date Deposited: 25 Nov 2022 07:30
Last Modified: 25 Nov 2022 07:30
URI: https://repository.unikom.ac.id/id/eprint/69450

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