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1 Optical Music Recognition and Data Import/Export Music 253/ CS 275A Eleanor Selfridge-Field.

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Presentation on theme: "1 Optical Music Recognition and Data Import/Export Music 253/ CS 275A Eleanor Selfridge-Field."— Presentation transcript:

1 1 Optical Music Recognition and Data Import/Export Music 253/ CS 275A Eleanor Selfridge-Field

2 Mus 253/CS 275A2 Optical Music Recognition History of efforts from c. 1968 CCARH survey in 1993-4: 37 projects, 7 responses Why is optical recognition difficult? Semantic meaning of many objects depends on graphical context, not purely on shape Sources and their legibility: Manuscripts: very irregular Out-of-copyright prints: images often deteriorated In-copyright prints: not legal to copy Errors in source Biggest problems for OMR developers Superimposition of objects in 2D image Constraints imposed by output formats

3 Mus 253/CS 275A3 Basic problems in optical data acquisition Image is crooked Elements of layout unconventional

4 Mus 253/CS 275A4 How does OMR work? Separation of lines and other matter Isolation of objects Recognition of objects Export to a format for storage, printing, sound, or data interchange Captured: notes, rests Missed: slurs, pedal marks

5 Mus 253/CS 275A5 Why is OMR difficult? Problems of image quality: Ideally Staff lines are straight Spacing is uniform The scanned material is clean (unspotted) Slurs are symmetrical Beams are parallel All lines are unbroken Reality is different! Problems of graphical context Some symbols affect the interpretation of pitch Key signatures Octave alterations   Some symbols affect the interpretation of duration Meter signatures Tempo indicators Fermatas  Some symbols affect dynamics and technique Dynamics marks    Repetition of note-groups , of sections   Instrumental technique   

6 Mus 253/CS 275A6 More difficulties Multiple configurations for same objects Methods of evaluation uncertain How to evaluate musical accuracy Handicaps for post-processing Controls for input quality Comparison between different kinds of output Weighing speed against accuracy and usability InputCapture format Post- Processing Carter00:20SCORE9:20 CCARH2:30 + 7:05 MuseData00:15

7 Mus 253/CS 275A7 Close-up views of conventionally typeset music Surface imperfections

8 Mus 253/CS 275A8 Close-up views (2) Missing contextual information Graphic imperfections

9 Mus 253/CS 275A9 Close-up views (3) Dirt Variable presentation of comparable objects

10 Mus 253/CS 275A10 Close-up views (4) Touching objects Conventional presentations

11 Mus 253/CS 275A11 SharpEye: File operations Comes from Shetland Islands Source code available Exports to MusicXML Four-step process Capture a page image View the auto-image Correct the image Save/export the result Vis-à-vis MuseData: SE: score-based MD: part-based

12 Mus 253/CS 275A12 SharpEye: System edits

13 Mus 253/CS 275A13 SharpEye: Raw Capture

14 Mus 253/CS 275A14 SharpEye: Correcting the interpretation Edit mode: Captured image below Interpreted image above Live object in red Available symbols in red Step 1: Selection a portion the score to edit

15 Mus 253/CS 275A15 SharpEye: Scroll view

16 Mus 253/CS 275A16 SharpEye: Data-interchange options

17 Mus 253/CS 275A17 Other OMR Software Capella-scan: [capella] PhotoScore: [Sibelius] SmartScore:

18 Mus 253/CS 275A18 Samples from Library of Congress site

19 Mus 253/CS 275A19 Samples 2

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