short-paper

MuRET: a music recognition, encoding, and transcription tool

Authors:

Jorge Calvo-Zaragoza,

José M. IñestaAuthors Info & Claims

DLfM '18: Proceedings of the 5th International Conference on Digital Libraries for Musicology

Pages 52 - 56

https://doi.org/10.1145/3273024.3273029

Published: 28 September 2018 Publication History

Abstract

The transcription process from early and modern notation manuscripts to a structured digital encoding has been traditionally performed following a fully manual workflow. At most it has received some technological support in particular stages, like optical music recognition (OMR) of the source images, or transcription to modern notation with music edition applications. Currently, there is no mature and stable enough solution for the OMR problem, and the most used music editors do not support early notations, such as the mensural one. In this work, a new tool called MUsic Recognition, Encoding, and Transcription (MuRET) is introduced, which covers all transcription phases, from the manuscript source to the encoded digital content. MuRET is designed as a technology-focused research tool, allowing different processing approaches to be used, and producing both the expected transcribed contents in standard encodings and data for the study of the transcription process itself.

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Digital Library

Cited By

Graczyk SPiniarska ZKałamoniak MŁukaszewski TŁukasik E(2024)An Online Tool for Semi-Automatically Annotating Music Scores for Optical Music RecognitionProceedings of the 11th International Conference on Digital Libraries for Musicology10.1145/3660570.3660571(73-77)Online publication date: 27-Jun-2024
https://dl.acm.org/doi/10.1145/3660570.3660571
Rios-Vila AAlfaro-Contreras MValero-Mas JCalvo-Zaragoza J(2023)Few-Shot Music Symbol Classification via Self-Supervised Learning and Nearest NeighborPattern Recognition, Computer Vision, and Image Processing. ICPR 2022 International Workshops and Challenges10.1007/978-3-031-37731-0_8(93-107)Online publication date: 10-Aug-2023
https://doi.org/10.1007/978-3-031-37731-0_8
Thomae MCumming JFujinaga I(2022)Digitization of Choirbooks in GuatemalaProceedings of the 9th International Conference on Digital Libraries for Musicology10.1145/3543882.3543885(19-26)Online publication date: 28-Jul-2022
https://dl.acm.org/doi/10.1145/3543882.3543885
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MuRET: a music recognition, encoding, and transcription tool
1. Information systems
  1. Information systems applications

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cover image ACM Other conferences

DLfM '18: Proceedings of the 5th International Conference on Digital Libraries for Musicology

September 2018

101 pages

ISBN:9781450365222

DOI:10.1145/3273024

Program Chair:
Kevin Page
University of Oxford

Copyright © 2018 ACM.

Publication rights licensed to ACM. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 September 2018

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Short-paper

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Ministerio de Economía, Industria y Competitividad

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DLfM '18

DLfM '18: 5th International Conference on Digital Libraries for Musicology

September 28, 2018

Paris, France

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DLfM '18 Paper Acceptance Rate 14 of 27 submissions, 52%;

Overall Acceptance Rate 27 of 48 submissions, 56%

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Cited By

Graczyk SPiniarska ZKałamoniak MŁukaszewski TŁukasik E(2024)An Online Tool for Semi-Automatically Annotating Music Scores for Optical Music RecognitionProceedings of the 11th International Conference on Digital Libraries for Musicology10.1145/3660570.3660571(73-77)Online publication date: 27-Jun-2024
https://dl.acm.org/doi/10.1145/3660570.3660571
Rios-Vila AAlfaro-Contreras MValero-Mas JCalvo-Zaragoza J(2023)Few-Shot Music Symbol Classification via Self-Supervised Learning and Nearest NeighborPattern Recognition, Computer Vision, and Image Processing. ICPR 2022 International Workshops and Challenges10.1007/978-3-031-37731-0_8(93-107)Online publication date: 10-Aug-2023
https://doi.org/10.1007/978-3-031-37731-0_8
Thomae MCumming JFujinaga I(2022)Digitization of Choirbooks in GuatemalaProceedings of the 9th International Conference on Digital Libraries for Musicology10.1145/3543882.3543885(19-26)Online publication date: 28-Jul-2022
https://dl.acm.org/doi/10.1145/3543882.3543885
Castellanos FGallego ACalvo-Zaragoza JFujinaga I(2022)Domain adaptation for staff-region retrieval of music score imagesInternational Journal on Document Analysis and Recognition (IJDAR)10.1007/s10032-022-00411-w25:4(281-292)Online publication date: 10-Sep-2022
https://doi.org/10.1007/s10032-022-00411-w
Ríos-Vila AEsplà-Gomis MRizo DPonce de León PIñesta J(2021)Applying Automatic Translation for Optical Music Recognition’s Encoding StepApplied Sciences10.3390/app1109389011:9(3890)Online publication date: 25-Apr-2021
https://doi.org/10.3390/app11093890
Alfaro-Contreras MValero-Mas J(2021)Exploiting the Two-Dimensional Nature of Agnostic Music Notation for Neural Optical Music RecognitionApplied Sciences10.3390/app1108362111:8(3621)Online publication date: 17-Apr-2021
https://doi.org/10.3390/app11083621
Stoessel JCollins DBolland S(2020)Using Optical Music Recognition to Encode 17th-Century Music PrintsProceedings of the 7th International Conference on Digital Libraries for Musicology10.1145/3424911.3425517(1-9)Online publication date: 16-Oct-2020
https://dl.acm.org/doi/10.1145/3424911.3425517
Nuñez-Alcover Ade León PCalvo-Zaragoza J(2019)Glyph and Position Classification of Music Symbols in Early Music ManuscriptsPattern Recognition and Image Analysis10.1007/978-3-030-31321-0_14(159-168)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.1007/978-3-030-31321-0_14
Mateiu TGallego ACalvo-Zaragoza J(2019)Domain Adaptation for Handwritten Symbol Recognition: A Case of Study in Old Music ManuscriptsPattern Recognition and Image Analysis10.1007/978-3-030-31321-0_12(135-146)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.1007/978-3-030-31321-0_12

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