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Author (up) Arnau Baro; Alicia Fornes; Carles Badal edit   pdf
  Title Handwritten Historical Music Recognition by Sequence-to-Sequence with Attention Mechanism Type Conference Article
  Year 2020 Publication 17th International Conference on Frontiers in Handwriting Recognition Abbreviated Journal  
  Volume Issue Pages  
  Abstract 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.  
  Address Virtual ICFHR; September 2020  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ICFHR  
  Notes DAG; 600.140; 600.121 Approved no  
  Call Number Admin @ si @ BFB2020 Serial 3448  
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