  Tablature notation is widely used in popular music to transcribe and share
guitar musical content. As a complement to standard score notation, tablatures
transcribe performance gesture information including finger positions and a
variety of guitar-specific playing techniques such as slides,
hammer-on/pull-off or bends.This paper focuses on bends, which enable to
progressively shift the pitch of a note, therefore circumventing physical
limitations of the discrete fretted fingerboard. In this paper, we propose a
set of 25 high-level features, computed for each note of the tablature, to
study how bend occurrences can be predicted from their past and future
short-term context. Experiments are performed on a corpus of 932 lead guitar
tablatures of popular music and show that a decision tree successfully predicts
bend occurrences with an F1 score of 0.71 anda limited amount of false positive
predictions, demonstrating promising applications to assist the arrangement of
non-guitar music into guitar tablatures.
