As a universal expression of human creativity, music is capable of conveying great subtlety and complexity. Crucially, this complexity is not encoded in the score or in the sounds, but is rather construed in the mind of the listener in the form of nuanced ...
This dissertation on data-driven music theory is centered around curatorial practices concerning the creation, publication, and evaluation of large, expert-annotated symbolic datasets. With its primary interest in the harmony of European tonal music from i ...
The human ability to perceive and understand music is remarkable. From an unstructured stream of acoustic input it creates a wide range of experiences, from psycho-acoustic effects to emotional and aesthetic responses. One such set of phenomena is the expe ...
Organizing fingerings, i.e., choosing which fingers to press on which positions and strings, is a crucial step for playing the violin. As the violin fingering comprises several components, the mapping of a musical phrase to the corresponding fingering arra ...
This paper presents an overview of the epistemological grounding of the computational approach to musical syntax as a tool to advance our understanding of the cognitive underpinnings of the musical experience. From the proposed perspective, formulations of ...
This corpus study constitutes the first quantitative style analysis of Choro, a primarily instrumental music genre that emerged in Brazil at the end of the 19th century. We evaluate its description in a recent comprehensive textbook by transcribing the cho ...
In Western tonal music, voice leading (VL) and harmony are two central concepts influencing whether a musical sequence is perceived as well-formed. However, experimental studies have primarily focused on the effect of harmony on the cognitive processing of ...
Music is hierarchically structured, both in how it is perceived by listeners and how it is composed. Such structure can be elegantly captured using probabilistic grammatical models similar to those used to study natural language. They address the complexit ...
This thesis proposes to analyse symbolic musical data under a statistical viewpoint, using state-of-the-art machine learning techniques. Our main argument is to show that it is possible to design generative models that are able to predict and to generate m ...
