Print Email Facebook Twitter An Analysis of Music Perception Skills on Crowdsourcing Platforms Title An Analysis of Music Perception Skills on Crowdsourcing Platforms Author Samiotis, I.P. (TU Delft Web Information Systems) Qiu, S. (TU Delft Web Information Systems; Hunan Institute of Advanced Technology) Lofi, C. (TU Delft Web Information Systems) Yang, J. (TU Delft Web Information Systems) Gadiraju, Ujwal (TU Delft Web Information Systems) Bozzon, A. (TU Delft Web Information Systems; TU Delft Human-Centred Artificial Intelligence) Date 2022 Abstract 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. Subject human computationmusic annotationperceptual skillsmusic sophisticationknowledge crowdsourcing To reference this document use: http://resolver.tudelft.nl/uuid:c27dd076-2e92-4d84-ae95-7e9720d8d5c8 DOI https://doi.org/10.3389/frai.2022.828733 ISSN 2624-8212 Source Frontiers in Artificial Intelligence, 5 Part of collection Institutional Repository Document type journal article Rights © 2022 I.P. Samiotis, S. Qiu, C. Lofi, J. Yang, Ujwal Gadiraju, A. Bozzon Files PDF frai_05_828733.pdf 1.2 MB Close viewer /islandora/object/uuid:c27dd076-2e92-4d84-ae95-7e9720d8d5c8/datastream/OBJ/view