A comprehensive survey on deep music generation: Multi-level representations, algorithms, evaluations, and future directions
S Ji, J Luo, X Yang - arXiv preprint arXiv:2011.06801, 2020 - arxiv.org
The utilization of deep learning techniques in generating various contents (such as image,
text, etc.) has become a trend. Especially music, the topic of this paper, has attracted …
text, etc.) has become a trend. Especially music, the topic of this paper, has attracted …
Music composition with deep learning: A review
C Hernandez-Olivan, JR Beltran - Advances in speech and music …, 2022 - Springer
Generating a complex work of art such as a musical composition requires exhibiting a
certain level of creativity. This depends on a variety of factors that are related to the hierarchy …
certain level of creativity. This depends on a variety of factors that are related to the hierarchy …
Objective-reinforced generative adversarial networks (organ) for sequence generation models
GL Guimaraes, B Sanchez-Lengeling… - arXiv preprint arXiv …, 2017 - arxiv.org
In unsupervised data generation tasks, besides the generation of a sample based on
previous observations, one would often like to give hints to the model in order to bias the …
previous observations, one would often like to give hints to the model in order to bias the …
A review of generative adversarial networks (GANs) and its applications in a wide variety of disciplines: from medical to remote sensing
We look into Generative Adversarial Network (GAN), its prevalent variants and applications
in a number of sectors. GANs combine two neural networks that compete against one …
in a number of sectors. GANs combine two neural networks that compete against one …
Machine learning and artificial neural network accelerated computational discoveries in materials science
Artificial intelligence (AI) has been referred to as the “fourth paradigm of science,” and as
part of a coherent toolbox of data‐driven approaches, machine learning (ML) dramatically …
part of a coherent toolbox of data‐driven approaches, machine learning (ML) dramatically …
Snore-GANs: Improving automatic snore sound classification with synthesized data
One of the frontier issues that severely hamper the development of automatic snore sound
classification (ASSC) associates to the lack of sufficient supervised training data. To cope …
classification (ASSC) associates to the lack of sufficient supervised training data. To cope …
Toward interactive music generation: A position paper
Music generation using deep learning has received considerable attention in recent years.
Researchers have developed various generative models capable of imitating musical …
Researchers have developed various generative models capable of imitating musical …
Convolutional generative adversarial network, via transfer learning, for traditional scottish music generation
The concept of a Binary Multi-track Sequential Generative Adversarial Network
(BinaryMuseGAN) used for the generation of music has been applied and tested for various …
(BinaryMuseGAN) used for the generation of music has been applied and tested for various …
[PDF][PDF] Mahlernet: Unbounded orchestral music with neural networks
E Lousseief, B Sturm - the Nordic Sound and Music Computing …, 2019 - diva-portal.org
This paper presents MahlerNet, a deep recurrent neural network that models polyphonic
music sequences of arbitrary length with an arbitrary number of instruments. The data …
music sequences of arbitrary length with an arbitrary number of instruments. The data …
A survey of generative adversarial networks
K Zhu, X Liu, H Yang - 2018 Chinese Automation Congress …, 2018 - ieeexplore.ieee.org
Generative adversarial networks (GANs) coming from the game theory allow machines to
learn deep representations without extra training data. By training two adversarial networks …
learn deep representations without extra training data. By training two adversarial networks …