Information retrieval in metal music sub-genres

Koray Açıcı; Tunç Aşuroğlu; Hasan Oğul

doi:10.1109/SIU.2017.7960162

Information retrieval in metal music sub-genres

Koray Açıcı
, Tunç Aşuroğlu
, Hasan Oğul

Not published at VTT

Başkent University

Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review

1 Citation (Scopus)

Abstract

Digital music platforms use meta-data based information retrieval systems for offering songs to users for their own taste of music. According to this system, songs that are labeled by other users are compared to songs that user listened and similar labeled songs are retrived in the process. In this situtation, information retrieval is independent from song content and subjective. To achieve objectivity, content based information retrieval systems are needed. In this study, a content-based music retrieval system based on one dimensional local binary pattern features which are extracted from audio data is proposed. Instead of retrieving different music genres, retrieval is applied on metal music sub-genres which have not been studied before and results are reported.

Original language	English
Title of host publication	2017 25th Signal Processing and Communications Applications Conference, SIU 2017
Publisher	Wiley-IEEE Press
Number of pages	4
ISBN (Electronic)	978-1-5090-6494-6
ISBN (Print)	978-1-5090-6495-3
DOIs	https://doi.org/10.1109/SIU.2017.7960162
Publication status	Published - 18 May 2017
MoE publication type	A4 Article in a conference publication
Event	2017 25th Signal Processing and Communications Applications Conference (SIU) - Antalya, Turkey Duration: 15 May 2017 → 18 May 2017

Conference

Conference	2017 25th Signal Processing and Communications Applications Conference (SIU)
Period	15/05/17 → 18/05/17

Keywords

Metals
Histograms
Music information retrieval
Rocks
Mel frequency cepstral coefficient
Feature extraction
dynamic time warping
local binary pattern
information retrieval
metal music

Access to Document

10.1109/SIU.2017.7960162

Cite this

@inproceedings{a608fba4c0114eb1948db1c2724b8929,

title = "Information retrieval in metal music sub-genres",

abstract = "Digital music platforms use meta-data based information retrieval systems for offering songs to users for their own taste of music. According to this system, songs that are labeled by other users are compared to songs that user listened and similar labeled songs are retrived in the process. In this situtation, information retrieval is independent from song content and subjective. To achieve objectivity, content based information retrieval systems are needed. In this study, a content-based music retrieval system based on one dimensional local binary pattern features which are extracted from audio data is proposed. Instead of retrieving different music genres, retrieval is applied on metal music sub-genres which have not been studied before and results are reported.",

keywords = "Metals, Histograms, Music information retrieval, Rocks, Mel frequency cepstral coefficient, Feature extraction, dynamic time warping, local binary pattern, information retrieval, metal music",

author = "Koray A{\c c}ıcı and Tun{\c c} A{\c s}uroğlu and Hasan Oğul",

year = "2017",

month = may,

day = "18",

doi = "10.1109/SIU.2017.7960162",

language = "English",

isbn = "978-1-5090-6495-3",

booktitle = "2017 25th Signal Processing and Communications Applications Conference, SIU 2017",

publisher = "Wiley-IEEE Press",

address = "United States",

note = "2017 25th Signal Processing and Communications Applications Conference (SIU) ; Conference date: 15-05-2017 Through 18-05-2017",

}

TY - GEN

T1 - Information retrieval in metal music sub-genres

AU - Açıcı, Koray

AU - Aşuroğlu, Tunç

AU - Oğul, Hasan

PY - 2017/5/18

Y1 - 2017/5/18

N2 - Digital music platforms use meta-data based information retrieval systems for offering songs to users for their own taste of music. According to this system, songs that are labeled by other users are compared to songs that user listened and similar labeled songs are retrived in the process. In this situtation, information retrieval is independent from song content and subjective. To achieve objectivity, content based information retrieval systems are needed. In this study, a content-based music retrieval system based on one dimensional local binary pattern features which are extracted from audio data is proposed. Instead of retrieving different music genres, retrieval is applied on metal music sub-genres which have not been studied before and results are reported.

AB - Digital music platforms use meta-data based information retrieval systems for offering songs to users for their own taste of music. According to this system, songs that are labeled by other users are compared to songs that user listened and similar labeled songs are retrived in the process. In this situtation, information retrieval is independent from song content and subjective. To achieve objectivity, content based information retrieval systems are needed. In this study, a content-based music retrieval system based on one dimensional local binary pattern features which are extracted from audio data is proposed. Instead of retrieving different music genres, retrieval is applied on metal music sub-genres which have not been studied before and results are reported.

KW - Metals

KW - Histograms

KW - Music information retrieval

KW - Rocks

KW - Mel frequency cepstral coefficient

KW - Feature extraction

KW - dynamic time warping

KW - local binary pattern

KW - information retrieval

KW - metal music

UR - https://www.scopus.com/pages/publications/85026327622

U2 - 10.1109/SIU.2017.7960162

DO - 10.1109/SIU.2017.7960162

M3 - Conference article in proceedings

SN - 978-1-5090-6495-3

BT - 2017 25th Signal Processing and Communications Applications Conference, SIU 2017

PB - Wiley-IEEE Press

T2 - 2017 25th Signal Processing and Communications Applications Conference (SIU)

Y2 - 15 May 2017 through 18 May 2017

ER -

Information retrieval in metal music sub-genres

Abstract

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Keywords

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