Scriptoria: A Crowd-powered Music Transcription System

Ioannis Petros Samiotis; Christoph  Lofi; Shaad Alaka; Cynthia C. S. Liem; Alessandro Bozzon

doi:10.1145/3487553.3524252

Scriptoria: A Crowd-powered Music Transcription System

Ioannis Petros Samiotis, Christoph Lofi, Shaad Alaka, Cynthia C. S. Liem, Alessandro Bozzon

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

1 Citation (Scopus)

34 Downloads (Pure)

Abstract

In this demo we present Scriptoria, an online crowdsourcing system to tackle the complex transcription process of classical orchestral scores. The system’s requirements are based on experts’ feedback from classical orchestra members. The architecture enables an end- to-end transcription process (from PDF to MEI) using a scalable microtask design. Reliability, stability, task and UI design were also evaluated and improved through Focus Group Discussions. Finally, we gathered valuable comments on the transcription process it- self alongside future additions that could greatly enhance current practices in their field.

Original language	English
Title of host publication	WWW 2022 - Companion Proceedings of the Web Conference 2022
Editors	F. Laforest, R. Troncy, L. Médini, I. Herman
Place of Publication	New York
Publisher	Association for Computing Machinery (ACM)
Pages	256-259
Number of pages	4
ISBN (Print)	978-1-4503-9130-6
DOIs	https://doi.org/10.1145/3487553.3524252
Publication status	Published - 2022
Event	WWW ’22 Companion: The Web Conference: IW3C2 - Virtual event at Lyon, France Duration: 25 Apr 2022 → 29 Jun 2022

Conference

Conference	WWW ’22 Companion: The Web Conference
Country/Territory	France
City	Virtual event at Lyon
Period	25/04/22 → 29/06/22

Keywords

crowdsourcing
music transcription
focus group discussions
iterative design
digital archives

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10.1145/3487553.3524252

3487553.3524252Final published version, 1.05 MBLicence: CC BY

Cite this

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title = "Scriptoria: A Crowd-powered Music Transcription System",

abstract = "In this demo we present Scriptoria, an online crowdsourcing system to tackle the complex transcription process of classical orchestral scores. The system{\textquoteright}s requirements are based on experts{\textquoteright} feedback from classical orchestra members. The architecture enables an end- to-end transcription process (from PDF to MEI) using a scalable microtask design. Reliability, stability, task and UI design were also evaluated and improved through Focus Group Discussions. Finally, we gathered valuable comments on the transcription process it- self alongside future additions that could greatly enhance current practices in their field. ",

keywords = "crowdsourcing, music transcription, focus group discussions, iterative design, digital archives",

author = "Samiotis, {Ioannis Petros} and Christoph Lofi and Shaad Alaka and Liem, {Cynthia C. S.} and Alessandro Bozzon",

year = "2022",

doi = "10.1145/3487553.3524252",

language = "English",

isbn = "978-1-4503-9130-6",

pages = "256--259",

editor = "F. Laforest and R. Troncy and L. M{\'e}dini and I. Herman",

booktitle = "WWW 2022 - Companion Proceedings of the Web Conference 2022",

publisher = "Association for Computing Machinery (ACM)",

address = "United States",

note = "WWW {\textquoteright}22 Companion: The Web Conference : IW3C2 ; Conference date: 25-04-2022 Through 29-06-2022",

}

Samiotis, IP , Lofi, C, Alaka, S, Liem, CCS & Bozzon, A 2022, Scriptoria: A Crowd-powered Music Transcription System. in F Laforest, R Troncy, L Médini & I Herman (eds), WWW 2022 - Companion Proceedings of the Web Conference 2022. Association for Computing Machinery (ACM), New York, pp. 256-259, WWW ’22 Companion: The Web Conference, Virtual event at Lyon, France, 25/04/22. https://doi.org/10.1145/3487553.3524252

Scriptoria: A Crowd-powered Music Transcription System. / Samiotis, Ioannis Petros ; Lofi, Christoph ; Alaka, Shaad et al.
WWW 2022 - Companion Proceedings of the Web Conference 2022. ed. / F. Laforest; R. Troncy; L. Médini; I. Herman. New York: Association for Computing Machinery (ACM), 2022. p. 256-259.

Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review

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AU - Bozzon, Alessandro

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AB - In this demo we present Scriptoria, an online crowdsourcing system to tackle the complex transcription process of classical orchestral scores. The system’s requirements are based on experts’ feedback from classical orchestra members. The architecture enables an end- to-end transcription process (from PDF to MEI) using a scalable microtask design. Reliability, stability, task and UI design were also evaluated and improved through Focus Group Discussions. Finally, we gathered valuable comments on the transcription process it- self alongside future additions that could greatly enhance current practices in their field.

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M3 - Conference contribution

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BT - WWW 2022 - Companion Proceedings of the Web Conference 2022

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PB - Association for Computing Machinery (ACM)

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Scriptoria: A Crowd-powered Music Transcription System

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