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Author (up) Arnau Baro; Pau Riba; Jorge Calvo-Zaragoza; Alicia Fornes edit   pdf
doi  isbn
  Title Optical Music Recognition by Long Short-Term Memory Networks Type Book Chapter
  Year 2018 Publication Graphics Recognition. Current Trends and Evolutions Abbreviated Journal  
  Volume 11009 Issue Pages 81-95  
  Keywords Optical Music Recognition; Recurrent Neural Network; Long ShortTerm Memory  
  Abstract 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.  
  Corporate Author Thesis  
  Publisher Springer Place of Publication Editor A. Fornes, B. Lamiroy  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-030-02283-9 Medium  
  Area Expedition Conference GREC  
  Notes DAG; 600.097; 601.302; 601.330; 600.121 Approved no  
  Call Number Admin @ si @ BRC2018 Serial 3227  
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