Add to ORKGMuch of the work on perception and understanding of music by computers has focused on low-level perceptual features such as pitch and tempo. Our work demonstrates that machine learning can be used to build eective style classiers for interactive performance systems. We also present an anal-ysis explaining why these techniques work so well when hand-coded approaches have consistently failed. We also describe a reliable real-time performance style classier.
Research applying machine learning to music modeling and generation typically proposes model archite...
Modelling human perception of musical similarity is critical for the evaluation of generative music ...
Recent literature has demonstrated the difficulty of classifying between composers who write in extr...
Much of the work on perception and understanding of music by computers has focused on low-level perc...
Much of the work on perception and understanding of music by computers has focused on low-level perc...
The use of artificial intelligence is common in the research of musicology, which involves the large...
Expressive musical performing style involves more than what is simply represented on the score. Perf...
Computational approaches to music composition and style imitation have engaged musicians, music scho...
Expressive musical performing style involves more than what is simply represented on the score. Perf...
In this paper we address the problem of musical style classification. This problem has several appli...
We present an overview of machine learning (ML) techniques and theirapplication in interactive music...
Machine learning is the capacity of a computational system to learn structures from datasets in orde...
Style recognition is one of the problems mostly faced by Computational Intelligence techniques. Most...
Computational Intelligence in Arts is a recent area of research. There is a growing interest in the ...
In this paper we address the problem of musical style classification, which has a number of applicat...
Research applying machine learning to music modeling and generation typically proposes model archite...
Modelling human perception of musical similarity is critical for the evaluation of generative music ...
Recent literature has demonstrated the difficulty of classifying between composers who write in extr...
Much of the work on perception and understanding of music by computers has focused on low-level perc...
Much of the work on perception and understanding of music by computers has focused on low-level perc...
The use of artificial intelligence is common in the research of musicology, which involves the large...
Expressive musical performing style involves more than what is simply represented on the score. Perf...
Computational approaches to music composition and style imitation have engaged musicians, music scho...
Expressive musical performing style involves more than what is simply represented on the score. Perf...
In this paper we address the problem of musical style classification. This problem has several appli...
We present an overview of machine learning (ML) techniques and theirapplication in interactive music...
Machine learning is the capacity of a computational system to learn structures from datasets in orde...
Style recognition is one of the problems mostly faced by Computational Intelligence techniques. Most...
Computational Intelligence in Arts is a recent area of research. There is a growing interest in the ...
In this paper we address the problem of musical style classification, which has a number of applicat...
Research applying machine learning to music modeling and generation typically proposes model archite...
Modelling human perception of musical similarity is critical for the evaluation of generative music ...
Recent literature has demonstrated the difficulty of classifying between composers who write in extr...