Handwritten Historical Music Recognition by Sequence-to-Sequence with Attention Mechanism

Arnau Baró*, Alícia Fornes, Carles Badal

*Autor corresponent d’aquest treball

Producció científica: Altres contribucions

19 Cites (Scopus)

Resum

Despite decades of research in Optical Music Recognition (OMR), the recognition of old handwritten music scores remains a challenge because of the variabilities in the handwriting styles, paper degradation, lack of standard notation, etc. Therefore, the research in OMR systems adapted to the particularities of old manuscripts is crucial to accelerate the conversion of music scores existing in archives into digital libraries, fostering the dissemination and preservation of our music heritage. In this paper we explore the adaptation of sequence-to-sequence models with attention mechanism (used in translation and handwritten text recognition) and the generation of specific synthetic data for recognizing old music scores. The experimental validation demonstrates that our approach is promising, especially when compared with long short-term memory neural networks.

Idioma originalEnglish
Nombre de pàgines6
ISBN (electrònic)978-1-7281-9966-5
DOIs
Estat de la publicacióPublicada - 2020

Sèrie de publicacions

NomInternational Conference on Handwriting Recognition
EditorIEEE COMPUTER SOC
ISSN (imprès)2167-6445

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