A new way to understand expressive interaction, focusing on the dynamic, fast, pre-reflective
processes underlying interactions with music. The expressive moment is that point in time …

We introduce a dataset for facilitating audio-visual analysis of music performances. The
dataset comprises 44 simple multi-instrument classical music pieces assembled from …

This book is the first ever to focus on the emerging field of self-aware computing from an
engineering perspective. It first comprehensively introduces fundamentals for self …

Machine learning is the capacity of a computational system to learn structures from datasets
in order to make predictions on newly seen data. Such an approach offers a significant …

We present an overview of machine learning (ML) techniques and their application in
interactive music and new digital instrument design. We first provide the non-specialist …

Musicians' sway during performance seems to be related to musical structure. However, it
has yet to be shown that examples of the relationship are not simply due to chance …

In this work we evaluate the gesture consistency of 13 clarinetists during several
performances. The goal is to establish an objective relation between their expressive …

This paper documents the development of ml. lib: a set of opensource tools designed for
employing a wide range of machine learning techniques within two popular real-time …

We propose a hierarchical approach for the design of gesture-to-sound mappings, with the
goal to take into account multilevel time structures in both gesture and sound processes …

Designing the relationship between motion and sound is essential to the creation of
interactive systems. This thesis proposes an approach to the design of the mapping between …