Digital advances have transformed the face of automatic music generation since its
beginnings at the dawn of computing. Despite the many breakthroughs, issues such as the …

Up to now, there has only been little work on using features from temporal approximations of
signals for audio recognition. Time-frequency tradeoffs are an important issue in signal …

VirtualBand is a multi-agent system dedicated to live computer-enhanced music
performances. VirtualBand enables one or several musicians to interact in real-time with …

Guided by the idea that musical human-computer interaction may become more effective,
intuitive, and creative when basing its computer part on cognitively more plausible learning …

Variable Length Markov Chains with Exogenous Covariates (VLMCX) are stochastic models
that use Generalized Linear Models to compute transition probabilities, taking into account …

A system is presented that learns the structure of an audio recording of a rhythmical
percussion fragment in an unsupervised manner and that synthesizes musical variations …

ABSTRACT A system is presented that generates a sound sequence from an original audio
chord sequence, having the following characteristics: The generation can be arbitrarily long …

A framework is proposed for generating interesting, musically similar variations of a given
monophonic melody. The focus is on pop/rock guitar and bass guitar melodies with the aim …

Data-driven sequence models have long played a role in the analysis and generation of
musical information. Such models are of interest in computational musicology, computer …

This thesis introduces timbre transformations by means of deep learning. A set of
convolutional autoencoders is created to deal with the task. Each structure uses …