Improving rhythmic transcriptions via probability models applied post-OMR
Name
b2caa923bc8a8331261a3722d537efe776ba.pdf
Description
Published version
Size
1.59 MB
Format
Unknown
Checksum (MD5)
b6ac4e5e57ac2399b3d9031713dec17a
Author(s)
Cuthbert, Michael Scott
Date Issued
2014
Journal
Proceedings of the 15th International Society for Music Information Retrieval Conference, ISMIR 2014, Taipei, Taiwan, October 27-31, 2014
Citation
Church, Maura and Michael Cuthbert. 2014. "Improving rhythmic transcriptions via probability models applied post-OMR." Proceedings of the 15th International Society for Music Information Retrieval Conference, ISMIR 2014, Taipei, Taiwan, October 27-31, 2014.
Version
Final published version
Abstract
© Maura Church, Michael Scott Cuthbert. Despite many improvements in the recognition of graphical elements, even the best implementations of Optical Music Recognition (OMR) introduce inaccuracies in the resultant score. These errors, particularly rhythmic errors, are time consuming to fix. Most musical compositions repeat rhythms between parts and at various places throughout the score. Information about rhythmic self-similarity, however, has not previously been used in OMR systems. This paper describes and implements methods for using the prior probabilities for rhythmic similarities in scores produced by a commercial OMR system to correct rhythmic errors which cause a contradiction between the notes of a measure and the underlying time signature. Comparing the OMR output and post-correction results to hand-encoded scores of 37 polyphonic pieces and movements (mostly drawn from the classical repertory), the system reduces incorrect rhythms by an average of 19% (min: 2%, max: 36%). The paper includes a public release of an implementation of the model in music21 and also suggests future refinements and applications to pitch correction that could further improve the accuracy of OMR systems.
MIT Department
Massachusetts Institute of Technology. Music and Theater Arts Section
Terms of Use
Creative Commons Attribution 4.0 International license
Persistent DSpace Link
DOI of Published Version
http://www.terasoft.com.tw/conf/ismir2014/proceedings/T116_357_Paper.pdf
