Hybrid Annotation Systems for Music Transcription

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

Abstract

Automated methods and human annotation are being extensively utilized to scale up modern classification systems. Processes though such as music transcription, oppose certain challenges due to the complexity of the domain and the expertise needed to read and process music scores. In this work, we examine how music transcription could benefit from systems that utilize hybrid annotation workflows, where automated methods are being trained, evaluated or have their output fixed by crowdworkers, using microtask designs. We argue that through careful task design utilizing microtask crowdsourcing principles, the general crowd can meaningfully contribute to such hybrid transcription systems.
Original languageEnglish
Title of host publication3rd International Workshop on Reading Music Systems
EditorsJorge Calvo-Zaragoza, Alexander Pacha
Pages23-
Publication statusPublished - 2021
Event3rd International Workshop on
Reading Music Systems
- Alicante, Spain
Duration: 23 Jul 202123 Jul 2021

Conference

Conference3rd International Workshop on
Reading Music Systems
CountrySpain
CityAlicante
Period23/07/2123/07/21

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