Tan Hakan Ozaslan / Josep Lluis Arcos
smcnetwork.org/files/proceedings/20
Understanding the gap between a musical score and a real performance of that score is still a challenging problem. To tackle this broad problem, researchers focus on specific instruments and/or musical styles. Hence, our research is focused on the study of classical guitar and aims at designing a system able to model the use of the expressive resources of that instrument. Thus, one of the first goals of our research is to provide a tool able to automatically identify expressive resources in the context of real recordings. In this paper we present some preliminary results on the identification of two classical guitar articulations from a collection of chromatic exercises recorded by a professional guitarist. Specifically, our system combines several state of the art analysis algorithms to distinguish among
two similar guitarists’ left hand articulations such as legato and glissando. We report some experiments and analyze the results achieved with our approach
Legato and glissando identification in classical guitar
