Classical Music Clustering Based on Acoustic Features

Autor:	Wang, Xindi, Haque, Syed Arefinul
Rok vydání:	2017
Předmět:	Computer Science - Information Retrieval Computer Science - Learning Computer Science - Sound
Druh dokumentu:	Working Paper
Popis:	In this paper we cluster 330 classical music pieces collected from MusicNet database based on their musical note sequence. We use shingling and chord trajectory matrices to create signature for each music piece and performed spectral clustering to find the clusters. Based on different resolution, the output clusters distinctively indicate composition from different classical music era and different composing style of the musicians.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1706.08928 Zobrazit plný text záznamu View this record from Arxiv