Guitar Chord Diagram Suggestion for Western Popular Music

Chord diagrams are used by guitar players to show where and how to play a chord on the fretboard. They are useful to beginners learning chords or for sharing the hand positions required to play a song.However, the diagrams presented on guitar learning toolsare usually selected from an existing databaseand rarely represent the actual positions used by performers.In this paper, we propose a tool which suggests a chord diagram for achord label,taking into account the diagram of the previous chord.Based on statistical analysis of the DadaGP and mySongBook datasets, we show that some chord diagrams are over-represented in western popular musicand that some chords can be played in more than 20 different ways.We argue that taking context into account can improve the variety and the quality of chord diagram suggestion, and compare this approach with a model taking only the current chord label into account.We show that adding previous context improves the F1-score on this task by up to 27% and reduces the propensity of the model to suggest standard open chords.We also define the notion of texture in the context of chord diagrams andshow through a variety of metrics that our model improves textureconsistencywith the previous diagram.

Modeling Bends in Popular Music Guitar Tablatures

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.