This article describes the M ́egra music system, a code-based, stochastic music system that can be used in a live performance context, as well as for longer compositions. M ́egra relies on Probabilistic Finite Automata (PFA) as its fundamental data structure. A case is made for the use of PFAs as a data model that can not only be trained(in the sense of machine learning), but also be interacted with on the basis of predefined operations and, as a side effect, enables one to creatively use the imperfections that occur when using very small datasets to infer musical sequence generators with the help of machine learning method
Algorithmic music composition is a popular area of research in computer aided music; it is the appli...
The systems acquire musical knowledge by inductive learning and learn key features of a musical data...
This thesis presents several hierarchical generative Bayesian models of musical signals designed to ...
The procreative statistical framework of musical note structures produces a crucial role in multimed...
Autoregressive Time Series Analysis (TSA) of music can model aspects of its acoustic features, struc...
Live coding is the creative act of interactive code evaluations and multimodal assessments during th...
Research applying machine learning to music modeling and generation typically proposes model archite...
Natural systems are the source of inspiration for the human tendency to pursue creative endeavors. ...
The aim of this thesis is to review the current state of machine learning in music composition and t...
Beyond solving daily logical problems, this project seeks to employ Artificial Intelligence in music...
Music is a phenomenon common in most human cultures. In a lot of cases, music is played as an accomp...
Random generation of music goes back at least to the 1700s with the introduction of Musical Dice Gam...
This work presents a novel approach for the design of a predictive model of music that can be used t...
International audienceAnalyzing and formalizing the intricate mechanisms of music is a very challeng...
We present a reproducible music information retrieval (MIR) study on 133 performances from the 10th ...
Algorithmic music composition is a popular area of research in computer aided music; it is the appli...
The systems acquire musical knowledge by inductive learning and learn key features of a musical data...
This thesis presents several hierarchical generative Bayesian models of musical signals designed to ...
The procreative statistical framework of musical note structures produces a crucial role in multimed...
Autoregressive Time Series Analysis (TSA) of music can model aspects of its acoustic features, struc...
Live coding is the creative act of interactive code evaluations and multimodal assessments during th...
Research applying machine learning to music modeling and generation typically proposes model archite...
Natural systems are the source of inspiration for the human tendency to pursue creative endeavors. ...
The aim of this thesis is to review the current state of machine learning in music composition and t...
Beyond solving daily logical problems, this project seeks to employ Artificial Intelligence in music...
Music is a phenomenon common in most human cultures. In a lot of cases, music is played as an accomp...
Random generation of music goes back at least to the 1700s with the introduction of Musical Dice Gam...
This work presents a novel approach for the design of a predictive model of music that can be used t...
International audienceAnalyzing and formalizing the intricate mechanisms of music is a very challeng...
We present a reproducible music information retrieval (MIR) study on 133 performances from the 10th ...
Algorithmic music composition is a popular area of research in computer aided music; it is the appli...
The systems acquire musical knowledge by inductive learning and learn key features of a musical data...
This thesis presents several hierarchical generative Bayesian models of musical signals designed to ...