TY - JOUR
T1 - An Analysis of Music Perception Skills on Crowdsourcing Platforms
AU - Samiotis, Ioannis Petros
AU - Qiu, Sihang
AU - Lofi, Christoph
AU - Yang, Jie
AU - Gadiraju, Ujwal
AU - Bozzon, Alessandro
PY - 2022
Y1 - 2022
N2 - Music content annotation campaigns are common on paid crowdsourcing platforms. Crowd workers are expected to annotate complex music artifacts, a task often demanding specialized skills and expertise, thus selecting the right participants is crucial for campaign success. However, there is a general lack of deeper understanding of the distribution of musical skills, and especially auditory perception skills, in the worker population. To address this knowledge gap, we conducted a user study (N = 200) on Prolific and Amazon Mechanical Turk. We asked crowd workers to indicate their musical sophistication through a questionnaire and assessed their music perception skills through an audio-based skill test. The goal of this work is to better understand the extent to which crowd workers possess higher perceptions skills, beyond their own musical education level and self reported abilities. Our study shows that untrained crowd workers can possess high perception skills on the music elements of melody, tuning, accent, and tempo; skills that can be useful in a plethora of annotation tasks in the music domain.
AB - Music content annotation campaigns are common on paid crowdsourcing platforms. Crowd workers are expected to annotate complex music artifacts, a task often demanding specialized skills and expertise, thus selecting the right participants is crucial for campaign success. However, there is a general lack of deeper understanding of the distribution of musical skills, and especially auditory perception skills, in the worker population. To address this knowledge gap, we conducted a user study (N = 200) on Prolific and Amazon Mechanical Turk. We asked crowd workers to indicate their musical sophistication through a questionnaire and assessed their music perception skills through an audio-based skill test. The goal of this work is to better understand the extent to which crowd workers possess higher perceptions skills, beyond their own musical education level and self reported abilities. Our study shows that untrained crowd workers can possess high perception skills on the music elements of melody, tuning, accent, and tempo; skills that can be useful in a plethora of annotation tasks in the music domain.
KW - human computation
KW - music annotation
KW - perceptual skills
KW - music sophistication
KW - knowledge crowdsourcing
U2 - 10.3389/frai.2022.828733
DO - 10.3389/frai.2022.828733
M3 - Article
SN - 2624-8212
VL - 5
JO - Frontiers in Artificial Intelligence
JF - Frontiers in Artificial Intelligence
M1 - 828733
ER -