Further Steps towards a Standard Testbed for Optical Music Recognition

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F16%3A10335467" target="_blank" >RIV/00216208:11320/16:10335467 - isvavai.cz</a>

Výsledek na webu

<a href="https://18798-presscdn-pagely.netdna-ssl.com/ismir2016/wp-content/uploads/sites/2294/2016/07/289_Paper.pdf" target="_blank" >https://18798-presscdn-pagely.netdna-ssl.com/ismir2016/wp-content/uploads/sites/2294/2016/07/289_Paper.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Further Steps towards a Standard Testbed for Optical Music Recognition

Popis výsledku v původním jazyce

Evaluating Optical Music Recognition (OMR) is notoriously difficult and automated end-to-end OMR evaluation metrics are not available to guide development. In "Towards a Standard Testbed for Optical Music Recognition: Definitions, Metrics, and Page Images", Byrd and Simonsen recently stress that a benchmarking standard is needed in the OMR community, both with regards to data and evaluation metrics. We build on their analysis and definitions and present a prototype of an OMR benchmark. We do not, however, presume to present a complete solution to the complex problem of OMR benchmarking. Our contributions are: (a) an attempt to define a multi- level OMR benchmark dataset and a practical prototype implementation for both printed and handwritten scores, (b) a corpus-based methodology for assessing automated evaluation metrics, and an underlying corpus of over 1000 qualified relative cost-to-correct judgments. We then assess several straightforward automated MusicXML evaluation metrics against this corpus

Název v anglickém jazyce

Further Steps towards a Standard Testbed for Optical Music Recognition

Popis výsledku anglicky

Evaluating Optical Music Recognition (OMR) is notoriously difficult and automated end-to-end OMR evaluation metrics are not available to guide development. In "Towards a Standard Testbed for Optical Music Recognition: Definitions, Metrics, and Page Images", Byrd and Simonsen recently stress that a benchmarking standard is needed in the OMR community, both with regards to data and evaluation metrics. We build on their analysis and definitions and present a prototype of an OMR benchmark. We do not, however, presume to present a complete solution to the complex problem of OMR benchmarking. Our contributions are: (a) an attempt to define a multi- level OMR benchmark dataset and a practical prototype implementation for both printed and handwritten scores, (b) a corpus-based methodology for assessing automated evaluation metrics, and an underlying corpus of over 1000 qualified relative cost-to-correct judgments. We then assess several straightforward automated MusicXML evaluation metrics against this corpus

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/GBP103%2F12%2FG084" target="_blank" >GBP103/12/G084: Centrum pro multi-modální interpretaci dat velkého rozsahu</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2016

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 17th International Society for Music Information Retrieval Conference

ISBN

978-0-692-75506-8

ISSN

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e-ISSN

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Počet stran výsledku

7

Strana od-do

157-163

Název nakladatele

New York University

Místo vydání

New York, USA

Místo konání akce

New York, USA

Datum konání akce

7. 8. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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