CREATES - Convolutional Neural Network applied to Identification of Musical Elements in OMR
Resumo
Optical music recognition (OMR) is an important tool to recognize a scanned page of music sheet automatically, which has been applied to preserving music scores. In this paper, we present a comparative study among Convolutional Neural Network (CNN) and state-of-the-art classiers to classify musical symbols. The initial results show that the CNN is promising in this task according to provided information.
Palavras-chave:
Music Information Retrieval
Referências
Avner Maximiliano de Paulo, Flávio Luiz Schiavoni, Marcos Antônio de Matos Laia, and Daniel Luiz Alves Madeira. Copista-sistema de omr para a recuperaç ao de acervo histórico musical. XV SBCM-Computer Music: Beyond the frontiers of signal processing and computational models, 2015.
David Bainbridge and Tim Bell. The challenge of optical music recognition. Computers and the Humanities, 35(2):95–121, 2001.
Ana Rebelo and Jaime S Cardoso. Staff line detection and removal in the grayscale domain. In 2013 12th International Conference on Document Analysis and Recognition, pages 57–61. IEEE, 2013.
Christoph Dalitz, Michael Droettboom, Bastian Pranzas, and Ichiro Fujinaga. A comparative study of staff removal algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(5):753–766, 2008.
Ichiro Fujinaga. Staff detection and removal. In Visual Perception of Music Notation: On-Line and Off Line Recognition, pages 1–39. IGI Global, 2004.
Jaime dos Santos Cardoso, Artur Capela, Ana Rebelo, Carlos Guedes, and Joaquim Pinto da Costa. Staff detection with stable paths. IEEE Transactions on Pattern Analysis and Machine Intelligence, 31(6):1134–1139, 2009.
Florence Rossant and Isabelle Bloch. Robust and adaptive omr system including fuzzy modeling, fusion of musical rules, and possible error detection. EURASIP Journal on Advances in Signal Processing, 2007(1):081541, 2006.
Alicia Fornés, Josep Lladós, and Gemma Sánchez. Primitive segmentation in old handwritten music scores. In International Workshop on Graphics Recognition, pages 279– 290. Springer, 2005.
Cuihong Wen, Ana Rebelo, Jing Zhang, and Jaime Cardoso. A new optical music recognition system based on combined neural network. Pattern Recognition Letters, 58:1–7, 2015.
Ana Rebelo, G Capela, and Jaime S Cardoso. Optical recognition of music symbols. International Journal on Document Analysis and Recognition (IJDAR), 13(1):19– 31, 2010.
Alicia Fornés, Josep Lladós, and Gemma Sánchez. Old handwritten musical symbol classification by a dynamic time warping based method. In International Workshop on Graphics Recognition, pages 51–60. Springer, 2007.
David Bainbridge and Tim Bell. The challenge of optical music recognition. Computers and the Humanities, 35(2):95–121, 2001.
Ana Rebelo and Jaime S Cardoso. Staff line detection and removal in the grayscale domain. In 2013 12th International Conference on Document Analysis and Recognition, pages 57–61. IEEE, 2013.
Christoph Dalitz, Michael Droettboom, Bastian Pranzas, and Ichiro Fujinaga. A comparative study of staff removal algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30(5):753–766, 2008.
Ichiro Fujinaga. Staff detection and removal. In Visual Perception of Music Notation: On-Line and Off Line Recognition, pages 1–39. IGI Global, 2004.
Jaime dos Santos Cardoso, Artur Capela, Ana Rebelo, Carlos Guedes, and Joaquim Pinto da Costa. Staff detection with stable paths. IEEE Transactions on Pattern Analysis and Machine Intelligence, 31(6):1134–1139, 2009.
Florence Rossant and Isabelle Bloch. Robust and adaptive omr system including fuzzy modeling, fusion of musical rules, and possible error detection. EURASIP Journal on Advances in Signal Processing, 2007(1):081541, 2006.
Alicia Fornés, Josep Lladós, and Gemma Sánchez. Primitive segmentation in old handwritten music scores. In International Workshop on Graphics Recognition, pages 279– 290. Springer, 2005.
Cuihong Wen, Ana Rebelo, Jing Zhang, and Jaime Cardoso. A new optical music recognition system based on combined neural network. Pattern Recognition Letters, 58:1–7, 2015.
Ana Rebelo, G Capela, and Jaime S Cardoso. Optical recognition of music symbols. International Journal on Document Analysis and Recognition (IJDAR), 13(1):19– 31, 2010.
Alicia Fornés, Josep Lladós, and Gemma Sánchez. Old handwritten musical symbol classification by a dynamic time warping based method. In International Workshop on Graphics Recognition, pages 51–60. Springer, 2007.
Publicado
24/10/2021
Como Citar
BARBOSA, Jenaro Augusto; SANTOS, Edimilson Batista dos.
CREATES - Convolutional Neural Network applied to Identification of Musical Elements in OMR. In: SIMPÓSIO BRASILEIRO DE COMPUTAÇÃO MUSICAL (SBCM), 18. , 2021, Recife.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 221-224.
DOI: https://doi.org/10.5753/sbcm.2021.19452.
