TY  - CHAP
AU  - Arnau Baro
AU  - Pau Riba
AU  - Jorge Calvo-Zaragoza
AU  - Alicia Fornes
A2  - GREC
ED  - A. Fornes, B. Lamiroy
PY  - 2018//
TI  - Optical Music Recognition by Long Short-Term Memory Networks
T2  - LNCS
BT  - Graphics Recognition. Current Trends and Evolutions
SP  - 81
EP  - 95
VL  - 11009
PB  - Springer
KW  - Optical Music Recognition
KW  - Recurrent Neural Network
KW  - Long ShortTerm Memory
N2  - Optical Music Recognition refers to the task of transcribing the image of a music score into a machine-readable format. Many music scores are written in a single staff, and therefore, they could be treated as a sequence. Therefore, this work explores the use of Long Short-Term Memory (LSTM) Recurrent Neural Networks for reading the music score sequentially, where the LSTM helps in keeping the context. For training, we have used a synthetic dataset of more than 40000 images, labeled at primitive level. The experimental results are promising, showing the benefits of our approach.
SN  - 978-3-030-02283-9
L1  - http://refbase.cvc.uab.es/files/BRC2018.pdf
UR  - http://dx.doi.org/10.1007/978-3-030-02284-6_7
N1  - DAG; 600.097; 601.302; 601.330; 600.121
ID  - Arnau Baro2018
ER  -