most citedPOP909: A Pop-song Dataset for Music Arrangement Generation

52 citations · 112 across the 6 of their papers we have counts for

collaborators

6 papers

cs.SD202052 cited

POP909: A Pop-song Dataset for Music Arrangement Generation

Ziyu Wang, Ke Chen, Junyan Jiang +5

Music arrangement generation is a subtask of automatic music generation, which involves reconstructing and re-conceptualizing a piece with new compositional techniques. Such a gene…

cs.SD202020 cited

Learning Interpretable Representation for Controllable Polyphonic Music Generation

Ziyu Wang, Dingsu Wang, Yixiao Zhang +1

While deep generative models have become the leading methods for algorithmic composition, it remains a challenging problem to control the generation process because the latent vari…

eess.AS202021 cited

PIANOTREE VAE: Structured Representation Learning for Polyphonic Music

Ziyu Wang, Yiyi Zhang, Yixiao Zhang +4

The dominant approach for music representation learning involves the deep unsupervised model family variational autoencoder (VAE). However, most, if not all, viable attempts on thi…

cs.LG2020

Word Representation for Rhythms

Tongyu Lu, Lyucheng Yan, Gus Xia

This paper proposes a word representation strategy for rhythm patterns. Using 1034 pieces of Nottingham Dataset, a rhythm word dictionary whose size is 450 (without control tokens)…

cs.SD202015 cited

Continuous Melody Generation via Disentangled Short-Term Representations and Structural Conditions

Ke Chen, Gus Xia, Shlomo Dubnov

Automatic music generation is an interdisciplinary research topic that combines computational creativity and semantic analysis of music to create automatic machine improvisations.…

cs.SD20184 cited

A Framework for Automated Pop-song Melody Generation with Piano Accompaniment Arrangement

Ziyu Wang, Gus Xia

We contribute a pop-song automation framework for lead melody generation and accompaniment arrangement. The framework reflects the major procedures of human music composition, gene…