A survey on deep learning for symbolic music generation: Representations, algorithms, evaluations, and challenges

S Ji, X Yang, J Luo - ACM Computing Surveys, 2023 - dl.acm.org
Significant progress has been made in symbolic music generation with the help of deep
learning techniques. However, the tasks covered by symbolic music generation have not …

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 …

Giantmidi-piano: A large-scale midi dataset for classical piano music

Q Kong, B Li, J Chen, Y Wang - arXiv preprint arXiv:2010.07061, 2020 - arxiv.org
Symbolic music datasets are important for music information retrieval and musical analysis.
However, there is a lack of large-scale symbolic datasets for classical piano music. In this …

MidiBERT-piano: large-scale pre-training for symbolic music understanding

YH Chou, I Chen, CJ Chang, J Ching… - arXiv preprint arXiv …, 2021 - arxiv.org
This paper presents an attempt to employ the mask language modeling approach of BERT
to pre-train a 12-layer Transformer model over 4,166 pieces of polyphonic piano MIDI files …

Musicagent: An ai agent for music understanding and generation with large language models

D Yu, K Song, P Lu, T He, X Tan, W Ye, S Zhang… - arXiv preprint arXiv …, 2023 - arxiv.org
AI-empowered music processing is a diverse field that encompasses dozens of tasks,
ranging from generation tasks (eg, timbre synthesis) to comprehension tasks (eg, music …

The ethics of creative AI

C Flick, K Worrall - The Language of Creative AI: Practices, Aesthetics and …, 2022 - Springer
Creative AI has had and will continue to have immense impact on creative communities and
society more broadly. Along with the great power, these techniques provide and come …

[PDF][PDF] ATEPP: A dataset of automatically transcribed expressive piano performance

H Zhang, J Tang, S Rafee, S Dixon, G Fazekas… - 2023 - qmro.qmul.ac.uk
Computational models of expressive piano performance rely on attributes like tempo, timing,
dynamics and pedalling. Despite some promising models for performance assessment and …

Fine-grained position helps memorizing more, a novel music compound transformer model with feature interaction fusion

Z Li, R Gong, Y Chen, K Su - Proceedings of the AAAI Conference on …, 2023 - ojs.aaai.org
Due to the particularity of the simultaneous occurrence of multiple events in music
sequences, compound Transformer is proposed to deal with the challenge of long …

[PDF][PDF] Building the MetaMIDI Dataset: Linking Symbolic and Audio Musical Data.

J Ens, P Pasquier - ISMIR, 2021 - archives.ismir.net
ABSTRACT We introduce the MetaMIDI Dataset (MMD), a large scale collection of 436,631
MIDI files and metadata. MMD contains artist and title metadata for 221,504 MIDI files, and …

End-to-end Bayesian segmentation and similarity assessment of performed music tempo and dynamics without score information

C Guichaoua, P Lascabettes, E Chew - Music & Science, 2024 - journals.sagepub.com
Segmenting continuous sensory input into coherent segments and subsegments is an
important part of perception. Music is no exception. By shaping the acoustic properties of …