Our research focuses on understanding the expressive resources used by guitar players.
We are interested in analyzing and modeling the use of these expressive resources considering the musical structure of a piece, its musical genre, and the personal traits of the players.
To incrementally tackle with the complexity of the problem, we plan the construction of a repository with different types of recordings:
- Studio recordings of Guitar Exercises: The purpose of using these technical exercises is to allow a fine study of ideal expressive resources. We are using exercises from the book of Abel Carlevaro. The advantage of using Carlevaro's exercices is that they cover many finger/string combinations and that most of the professionals-students are familiar with them.
- Studio recordings of Guitar Pieces: This second group of recordings enables the study of expressive resources in the context of a musical piece but in a controlled environment.
- Real/Commercial recordings: Finally, we are also interested in analyzing the way expressive resources are exploited when guitar is used to perform solos in poly-instrument pieces.
Regarding gesture acquisition, our goal is to design a sensing system to allow the study of the gestures of the left hand fingers in guitar performances. The design is leaded by the following principles:
- Has to be able to capture from macro-scale changes (i.e. the presence of finger bars) to micro-scale changes (i.e. vibrato) in player’s movements.
- The sensors have to be non-intrusive to the player.
To collect gesture information we are designing an acquisition system based on capacitive sensors.
Additionally, we have started a collaboration with the CIRMMT Centre to model the gesture of a guitar player by using the Qualisys motion capture system.
One of the goals of this research is the analysis and modeling of left hand articulations in a guitar performance. Here, we describe the gesture analysis performed from collected data, using our proposed gesture acquisition system and, more recently, using the Qualisys motion capture system. The study, is divided in the following issues:
- Study of collected left hand articulations.
- Fingering analysis for the most commonly played chords.
- Analysis and modeling of hand movements from the data obtained by a Qualisys motion capture system.
More detailed information can be found here.
An important goal of our research is to provide a tool able to automatically identify and analyze expressive resources in the context of real recordings. To that purpose, we depart from the study presented by J. Norton in his Phd Dissertation.
The tool will combine new analysis algorithms together with several state of the art audio analysis algorithms. More detailed information can be found here.