Automatic difficulty level rating for guitar tablatures
Date of Publication
Bachelor of Science in Computer Science
College of Computer Studies
Defense Panel Member
Conrado D. Ruiz
This research tackles the problem of automating the ranking of a guitar tablature's di culty level. Building upon recent research, this project proposes several di culty features and investigates their in uence on a set of pre-rated set of pieces being used by an existing academic standard of music levels. The di culty features will be ranked according to their in uence on a music school's levelling criteria. Models for automatically rating tablature were built around these experiments with the goal of a web application that provides the di culty level of a tablature, with hopes of improving the ambiguous format that guitar tablatures present. The linear regression model chosen had an r-squared metric of 27.61% and was implemented in a tablature repository website.
Archives, The Learning Commons, 12F, Henry Sy Sr. Hall
1 computer optical disc ; 4 3/4 in.
Guitar music; Tablature (Music)
Go, G., Kim, Y., Shin, H., & Velarde, J. A. (2016). Automatic difficulty level rating for guitar tablatures. Retrieved from https://animorepository.dlsu.edu.ph/etd_bachelors/10738