Chordify Annotator Subjectivity Dataset

Hendrik Vincent Koops; W.B. de Haas; A. Volk; J. Bransen; John Ashley Burgoyne

Chordify Annotator Subjectivity Dataset

Hendrik Vincent Koops, W.B. de Haas, A. Volk, J. Bransen, John Ashley Burgoyne

Music Cognition Group, University of Amsterdam

Research output: Contribution to conference › Other › Other research output

Abstract

Reference annotation datasets containing harmony annotations are at the core of a wide range of studies in music information retrieval and related fields. The majority of these datasets contain single reference annotations describing the harmony of each piece or song. Nevertheless, music theoretical insights on harmonic ambiguity and studies showing differences among annotators in many MIR tasks make the notion of a single “ground-truth” reference annotation a tenuous one. In order to gain a better understanding of differences between harmony annotators, we introduce the Chordify Annotator Subjectivity Dataset (CASD) containing chord labels for fifty songs from four annotators.

Original language	English
Number of pages	2
Publication status	Published - 23 Oct 2017
Event	International Society for Music Information Retrieval Conference 2017 - National University of Singapore Research Institute (NUSRI), Suzhou, China Duration: 23 Oct 2017 → 27 Oct 2017 https://ismir2017.smcnus.org/

Conference

Conference	International Society for Music Information Retrieval Conference 2017
Abbreviated title	ISMIR 2017
Country/Territory	China
City	Suzhou
Period	23/10/17 → 27/10/17
Internet address	https://ismir2017.smcnus.org/

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https://ismir2017.smcnus.org/lbds/Koops2017.pdf

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title = "Chordify Annotator Subjectivity Dataset",

abstract = "Reference annotation datasets containing harmony annotations are at the core of a wide range of studies in music information retrieval and related fields. The majority of these datasets contain single reference annotations describing the harmony of each piece or song. Nevertheless, music theoretical insights on harmonic ambiguity and studies showing differences among annotators in many MIR tasks make the notion of a single “ground-truth” reference annotation a tenuous one. In order to gain a better understanding of differences between harmony annotators, we introduce the Chordify Annotator Subjectivity Dataset (CASD) containing chord labels for fifty songs from four annotators.",

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year = "2017",

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note = "International Society for Music Information Retrieval Conference 2017, ISMIR 2017 ; Conference date: 23-10-2017 Through 27-10-2017",

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TY - CONF

T1 - Chordify Annotator Subjectivity Dataset

AU - Koops, Hendrik Vincent

AU - de Haas, W.B.

AU - Volk, A.

AU - Bransen, J.

AU - Burgoyne, John Ashley

PY - 2017/10/23

Y1 - 2017/10/23

N2 - Reference annotation datasets containing harmony annotations are at the core of a wide range of studies in music information retrieval and related fields. The majority of these datasets contain single reference annotations describing the harmony of each piece or song. Nevertheless, music theoretical insights on harmonic ambiguity and studies showing differences among annotators in many MIR tasks make the notion of a single “ground-truth” reference annotation a tenuous one. In order to gain a better understanding of differences between harmony annotators, we introduce the Chordify Annotator Subjectivity Dataset (CASD) containing chord labels for fifty songs from four annotators.

AB - Reference annotation datasets containing harmony annotations are at the core of a wide range of studies in music information retrieval and related fields. The majority of these datasets contain single reference annotations describing the harmony of each piece or song. Nevertheless, music theoretical insights on harmonic ambiguity and studies showing differences among annotators in many MIR tasks make the notion of a single “ground-truth” reference annotation a tenuous one. In order to gain a better understanding of differences between harmony annotators, we introduce the Chordify Annotator Subjectivity Dataset (CASD) containing chord labels for fifty songs from four annotators.

M3 - Other

T2 - International Society for Music Information Retrieval Conference 2017

Y2 - 23 October 2017 through 27 October 2017

ER -

Chordify Annotator Subjectivity Dataset

Abstract

Conference

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