ABSTRACT
The goal of the Lester S. Levy Sheet Music Collection, Phase Two project is to develop tools, processes, and systems that facilitate collection ingestion through automated processes that reduce, but not necessarily eliminate human intervention[1]. One of the major components of this project is an optical music recognition (OMR) system[2] that extracts musical information and lyric text from the page images that comprise each piece in a collection. It is often the case, as it is with the Levy Collection, that lyrics embedded in music notation are written in a syllabicated form so that each syllable lines up with the note or notes to which it corresponds. Searching the syllabicated form of words, however, would be counterintuitive and cumbersome for end-users. This paper describes the evolution of a tool that, using a simple algorithm, rebuilds complete words from lyric syllables and, in ambiguous cases, provides feedback to the collection builder. This system will be integrated into the workflow of the Levy Sheet Music Collection, but has broad applicability for any project ingesting musical scores with lyrics.
- Choudhury, G. S. et al. Digital Workflow Management: The Lester S. Levy Digitized Collection of Sheet Music. First Monday, 5(6), June 2000Google Scholar
- Choudhury, G. S., et al. Strike Up the Score: Deriving Searchable and Playable Digital Formats from Sheet Music. D-Lib Magazine, 7(2), February 2001Google Scholar
- D. D. Palmer. A trainable rule-based algorithm for word segmentation. In P. R. Cohen and W. Wahlster, editors, Proceedings of the Thirty-Fifth Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics, pages 321--328, Somerset, New Jersey, 1997. Association for Computational Linguistics Google ScholarDigital Library
- N. Porter, editor. Webster's Revised Unabridged Dictionary. G and C. Merriam Co., 1913Google Scholar
- Proc. Perl Conference 2.0. An Algorithmic Approach to English Pluralization, 1998Google Scholar
- Project Gutenberg. http://promo.net/pg/Google Scholar
- Sproat, R., Shih, C., Gale, W., Chang, N. A Stochastic Finite-State Word-Segmentation Algorithm for Chinese. Computational Linguistics, 22(3), 1996 Google ScholarDigital Library
- The Mutopia Project. http://www.mutopiaproject.org/Google Scholar
Index Terms
- Enhancing access to the levy sheet music collection: reconstructing full-text lyrics from syllables
Recommendations
Computational Analysis of Jazz Music: Estimating Tonality through Chord Progression Distances
CSAE '23: Proceedings of the 7th International Conference on Computer Science and Application EngineeringCurrently, research in music informatics focuses extensively on music theory, particularly on the theoretical systems of Western classical music dating back to the 19th century. However, contemporary popular music genres such as pop, rock, and jazz often ...
A Query-by-Singing System for Retrieving Karaoke Music
This paper investigates the problem of retrieving karaoke music using query-by-singing techniques. Unlike regular CD music, where the stereo sound involves two audio channels that usually sound the same, karaoke music encompasses two distinct channels ...
Automatic transcription of flamenco singing from polyphonic music recordings
Automatic note-level transcription is considered one of the most challenging tasks in music information retrieval. The specific case of flamenco singing transcription poses a particular challenge due to its complex melodic progressions, intonation ...
Comments