Abstract
This research tackles the problem of automating the rating of a guitar tablature's difficulty level. Building upon recent research, this project proposes several difficulty features and investigates their influence on a set of prerated set of pieces being used by an existing standard of music levels. The difficulty features will be ranked according to their influence on a music school's leveling criteria. Models for automatically rating tablature were built around these experiments with the goal of a web application that provides the difficulty 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 23.57% and was implemented in a tablature repository website.
