Led by the success of neural style transfer on visual arts, there has been a rising trend very recently in the effort of music style transfer. However, "music style" is not yet a well-defined concept from a scientific point of view. The difficulty lies in the intrinsic multi-level and multi-modal character of music representation (which is very different from image representation). As a result, depending on their interpretation of "music style", current studies under the category of "music style transfer", are actually solving completely different problems that belong to a variety of sub-fields of Computer Music. Also, a vanilla end-to-end approach, which aims at dealing with all levels of music representation at once by directly adopting t...
This work is the result of the transfer of the author's musical experiences, perceptions and ideas t...
Music style translation aims to generate variations of existing pieces of music by altering the styl...
In this transformation we present a rhythmically constrained audio style transfer technique for auto...
Style transfer of polyphonic music recordings is a challenging task when considering the modeling of...
We introduce MIDI-VAE, a neural network model based on Variational Autoencoders that is capable of h...
Utilizing deep learning techniques to generate musical contents has caught wide attention in recent ...
We introduce MIDI-VAE, a neural network model based on Variational Autoencoders that is capable of h...
Style transfer using Generative adversarial networks (GANs) has been successful in recent publicatio...
Style transfer using Generative adversarial networks (GANs) has been successful in recent publicatio...
Selective remixing refers to altering an existing musical composition to create something new. The p...
Musical timbre transfer is the task of re-rendering the musical content of a given source using the ...
Research on style transfer and domain translation has clearly demonstrated the ability of deep learn...
In this paper we address the problem of musical style classification. This problem has several appli...
Based on the adaptive particle swarm algorithm and error backpropagation neural network, this paper ...
In this transformation we present a rhythmically constrained audio style transfer technique for auto...
This work is the result of the transfer of the author's musical experiences, perceptions and ideas t...
Music style translation aims to generate variations of existing pieces of music by altering the styl...
In this transformation we present a rhythmically constrained audio style transfer technique for auto...
Style transfer of polyphonic music recordings is a challenging task when considering the modeling of...
We introduce MIDI-VAE, a neural network model based on Variational Autoencoders that is capable of h...
Utilizing deep learning techniques to generate musical contents has caught wide attention in recent ...
We introduce MIDI-VAE, a neural network model based on Variational Autoencoders that is capable of h...
Style transfer using Generative adversarial networks (GANs) has been successful in recent publicatio...
Style transfer using Generative adversarial networks (GANs) has been successful in recent publicatio...
Selective remixing refers to altering an existing musical composition to create something new. The p...
Musical timbre transfer is the task of re-rendering the musical content of a given source using the ...
Research on style transfer and domain translation has clearly demonstrated the ability of deep learn...
In this paper we address the problem of musical style classification. This problem has several appli...
Based on the adaptive particle swarm algorithm and error backpropagation neural network, this paper ...
In this transformation we present a rhythmically constrained audio style transfer technique for auto...
This work is the result of the transfer of the author's musical experiences, perceptions and ideas t...
Music style translation aims to generate variations of existing pieces of music by altering the styl...
In this transformation we present a rhythmically constrained audio style transfer technique for auto...