Music information retrieval
JA Burgoyne, I Fujinaga… - A new companion to …, 2015 - Wiley Online Library
Music information retrieval (MIR) is “a multidisciplinary research endeavor that strives to
develop innovative content‐based searching schemes, novel interfaces, and evolving …
develop innovative content‐based searching schemes, novel interfaces, and evolving …
Unsupervised neural domain adaptation for document image binarization
Binarization is a well-known image processing task, whose objective is to separate the
foreground of an image from the background. One of the many tasks for which it is useful is …
foreground of an image from the background. One of the many tasks for which it is useful is …
Staff-line removal with selectional auto-encoders
AJ Gallego, J Calvo-Zaragoza - Expert Systems with Applications, 2017 - Elsevier
Staff-line removal is an important preprocessing stage as regards most Optical Music
Recognition systems. The common procedures employed to carry out this task involve …
Recognition systems. The common procedures employed to carry out this task involve …
A holistic approach for aligned music and lyrics transcription
In this paper, we present the Aligned Music Notation and Lyrics Transcription (AMNLT)
challenge, whose goal is to retrieve the content from document images of vocal music. This …
challenge, whose goal is to retrieve the content from document images of vocal music. This …
Handwritten music recognition for mensural notation: Formulation, data and baseline results
J Calvo-Zaragoza, AH Toselli… - 2017 14th IAPR …, 2017 - ieeexplore.ieee.org
Music is a key element for cultural transmission, and so large collections of music
manuscripts have been preserved over the centuries. In order to develop computational …
manuscripts have been preserved over the centuries. In order to develop computational …
Hybrid hidden Markov models and artificial neural networks for handwritten music recognition in mensural notation
J Calvo-Zaragoza, AH Toselli, E Vidal - Pattern Analysis and Applications, 2019 - Springer
In this paper, we present a hybrid approach using hidden Markov models (HMM) and
artificial neural networks to deal with the task of handwritten Music Recognition in mensural …
artificial neural networks to deal with the task of handwritten Music Recognition in mensural …
Staff, symbol and melody detection of medieval manuscripts written in square notation using deep fully convolutional networks
Even today, the automatic digitisation of scanned documents in general, but especially the
automatic optical music recognition (OMR) of historical manuscripts, still remains an …
automatic optical music recognition (OMR) of historical manuscripts, still remains an …
[PDF][PDF] The SEILS dataset: Symbolically encoded scores in modern-early notation for computational musicology
The automatic analysis of notated Renaissance music is restricted by a shortfall in codified
repertoire. Thousands of scores have been digitised by music libraries across the world, but …
repertoire. Thousands of scores have been digitised by music libraries across the world, but …
[PDF][PDF] Evaluating OMR on the Early Music Online Collection.
L Pugin, T Crawford - ISMIR, 2013 - aruspix.net
ABSTRACT The Early Music Online (EMO) collection consists of about 300 printed music
books of the sixteenth century held at the British Library. They were recently digitized from …
books of the sixteenth century held at the British Library. They were recently digitized from …
[PDF][PDF] Digital Document Image Retrieval Using Optical Music Recognition.
Optical music recognition (OMR) and optical character recognition (OCR) have traditionally
been used for document transcription—that is, extracting text or symbolic music from page …
been used for document transcription—that is, extracting text or symbolic music from page …