Document type
Bachelor thesisPublication date
Publication license
Please use this identifier to cite or link to this item: https://hdl.handle.net/2445/181119
Implementació d'un sistema no supervisat amb adaptació online per classificar música
Journal Title
Authors
Director/Tutor
Journal ISSN
Volume Title
Related resource
Abstract
[en] Nowadays, music is still an important part of our lives: every one of us listens to some kind of music. There are currently loads of different styles and, to keep them organized, musical analysis has become very important - either to classify them according to their genre or for being able to recommend listeners similar songs to the ones they usually listen to. In this project we propose a unsupervised system to classify songs into different genres and, when necessary, label new genres that may come up. To achieve that, we will create groups
from the Hierarchical clustering algorithm and, finally, classify and create new groups from the ECOC (Error-Correcting Output Codes) strategies.
Description
Treballs Finals de Grau d'Enginyeria Informàtica, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2020, Director: Sergio Escalera Guerrero
Subject (English)
Citation
Citation
YOON, Chan Yong. Implementació d'un sistema no supervisat amb adaptació online per classificar música. [consulted: 8 of August of 2026]. Available at: https://hdl.handle.net/2445/181119