7 citations · 11 across the 4 of their papers we have counts for
4 papers · 1 filter
DDSynth-RL: Audio Synthesizer Inversion via Discrete Diffusion with Reinforcement Learning
Tristan Wu, Daniel Chin, Junan Zhang +3
Synthesizer inversion is challenging for two main reasons: 1) Distinct parameter configurations can produce perceptually similar sounds. 2) Parameter-space losses often fail to ref…
Versatile Symbolic Music-for-Music Modeling via Function Alignment
Junyan Jiang, Daniel Chin, Liwei Lin +2
Many music AI models learn a map between music content and human-defined labels. However, many annotations, such as chords, can be naturally expressed within the music modality its…
Language Model Mapping in Multimodal Music Learning: A Grand Challenge Proposal
Daniel Chin, Gus Xia
We have seen remarkable success in representation learning and language models (LMs) using deep neural networks. Many studies aim to build the underlying connections among differen…
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…