Deep learning's shallow gains: A comparative evaluation of algorithms for automatic music generation

Z Yin, F Reuben, S Stepney, T Collins - Machine Learning, 2023 - Springer
Deep learning methods are recognised as state-of-the-art for many applications of machine
learning. Recently, deep learning methods have emerged as a solution to the task of …

3D-DCDAE: Unsupervised music latent representations learning method based on a deep 3d convolutional denoising autoencoder for music genre classification

L Qiu, S Li, Y Sung - Mathematics, 2021 - mdpi.com
With unlabeled music data widely available, it is necessary to build an unsupervised latent
music representation extractor to improve the performance of classification models. This …

A survey on artificial intelligence for music generation: Agents, domains and perspectives

C Hernandez-Olivan, J Hernandez-Olivan… - arXiv preprint arXiv …, 2022 - arxiv.org
Music is one of the Gardner's intelligences in his theory of multiple intelligences. How
humans perceive and understand music is still being studied and is crucial to develop …

Examining emotion perception agreement in live music performance

S Yang, CN Reed, E Chew… - IEEE transactions on …, 2021 - ieeexplore.ieee.org
Current music emotion recognition (MER) systems rely on emotion data averaged across
listeners and over time to infer the emotion expressed by a musical piece, often neglecting …

When in Rome: a meta-corpus of functional harmony

M Gotham, G Micchi, NN López… - Transactions of …, 2023 - durham-repository.worktribe.com
'When in Rome'brings together all human-made, computer-encoded, functional harmonic
analyses of music. This amounts in total to over 2,000 analyses of 1,500 distinct works. The …

Exploring emotions in Bach chorales: a multi-modal perceptual and data-driven study

E Parada-Cabaleiro, A Batliner… - Royal Society …, 2023 - royalsocietypublishing.org
The relationship between music and emotion has been addressed within several
disciplines, from more historico-philosophical and anthropological ones, such as musicology …

CorpusVis: Visual analysis of digital sheet music collections

M Miller, J Rauscher, DA Keim… - Computer Graphics …, 2022 - Wiley Online Library
Manually investigating sheet music collections is challenging for music analysts due to the
magnitude and complexity of underlying features, structures, and contextual information …

A dataset of symbolic texture annotations in mozart piano sonatas

L Couturier, L Bigo, F Levé - International Society for Music Information …, 2022 - hal.science
Musical scores are generally analyzed under different aspects, notably melody, harmony,
rhythm, but also through their texture, although this last concept is arguably more delicate to …

MIDI2vec: Learning MIDI embeddings for reliable prediction of symbolic music metadata

P Lisena, A Meroño-Peñuela, R Troncy - Semantic Web, 2022 - content.iospress.com
An important problem in large symbolic music collections is the low availability of high-
quality metadata, which is essential for various information retrieval tasks. Traditionally …

[HTML][HTML] Musicaiz: A python library for symbolic music generation, analysis and visualization

C Hernandez-Olivan, JR Beltran - SoftwareX, 2023 - Elsevier
In this article, we present musicaiz, an object-oriented library for analyzing, generating and
evaluating symbolic music. The submodules of the package allow the user to create …