activity
20182022
most citedPOP909: A Pop-song Dataset for Music Arrangement Generation

52 citations · 160 across the 18 of their papers we have counts for

collaborators

23 papers

cs.SD20221 cited

Vis2Mus: Exploring Multimodal Representation Mapping for Controllable Music Generation

Runbang Zhang, Yixiao Zhang, Kai Shao +2

In this study, we explore the representation mapping from the domain of visual arts to the domain of music, with which we can use visual arts as an effective handle to control musi…

cs.SD2022

Modeling Perceptual Loudness of Piano Tone: Theory and Applications

Yang Qu, Yutian Qin, Lecheng Chao +3

The relationship between perceptual loudness and physical attributes of sound is an important subject in both computer music and psychoacoustics. Early studies of "equal-loudness c…

cs.SD20223 cited

Learning Hierarchical Metrical Structure Beyond Measures

Junyan Jiang, Daniel Chin, Yixiao Zhang +1

Music contains hierarchical structures beyond beats and measures. While hierarchical structure annotations are helpful for music information retrieval and computer musicology, such…

cs.SD20223 cited

Domain Adversarial Training on Conditional Variational Auto-Encoder for Controllable Music Generation

Jingwei Zhao, Gus Xia, Ye Wang

The variational auto-encoder has become a leading framework for symbolic music generation, and a popular research direction is to study how to effectively control the generation pr…

cs.SD20228 cited

Beat Transformer: Demixed Beat and Downbeat Tracking with Dilated Self-Attention

Jingwei Zhao, Gus Xia, Ye Wang

We propose Beat Transformer, a novel Transformer encoder architecture for joint beat and downbeat tracking. Different from previous models that track beats solely based on the spec…

cs.SD20225 cited

Learning long-term music representations via hierarchical contextual constraints

Shiqi Wei, Gus Xia

Learning symbolic music representations, especially disentangled representations with probabilistic interpretations, has been shown to benefit both music understanding and generati…