Computational analysis of expressivity in classical guitar performances
The study of musical expressivity is an active field in sound and music computing. The research interest comes from different motivations: to understand or model musical expressivity; to identify the expressive resources that characterize an instrument, musical genre, or performer; or to build synthesis systems able to play expressively. To tackle this broad problem, researchers focus on specific instruments and/or musical styles. Hence, in this thesis we focused on the analysis of the expressivity in classical guitar and our aim is to model the use of expressive resources of the instrument. The foundations of all the methods used in this dissertation are based on techniques from the fields of information retrieval, machine learning, and signal processing. We combine several state of the art analysis algorithms in order to deal with modeling the use of the expressive resources. Classical guitar is an instrument characterized by the diversity of its timbral...
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