From the 1 of 18 linked papers with an AI index.
18 papers
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…
P-MUSE: Prompt-MIDI-Optional Model for Unified Instrumental Music Synthesis and Editing
Chong Jing, Junan Zhang, Jing Yang +3
MIDI-to-Music system renders the melody and rhythm of a target MIDI sequence into musical segment while cloning instrument timbre from a prompt recording. Existing systems typicall…
Anysynth:Zero-Shot Instrument Cloning via In-Context Learning and Asymmetric Hierarchical Guidance
Chong Jing, Junan Zhang, Jing Yang +3
The paper presents Anysynth, a diffusion‑transformer synthesizer that can render arbitrary target MIDI sequences with the timbre of an unseen instrument by directly conditioning on…
Frequency-Aware Self-Supervised Music Representation Learning
Yicheng Gu, Junan Zhang, Jerry Li +2
Self-supervised learning (SSL) has emerged as an essential paradigm for music information retrieval (MIR). While current SSL models achieve state-of-the-art performance across vari…
Aliasing-Free Neural Audio Synthesis
Yicheng Gu, Junan Zhang, Chaoren Wang +3
In neural audio synthesis, neural vocoders and codecs are models that reconstruct waveforms from acoustic and latent representations, which are essential to the resulting audio qua…
EigeNet: Geometry-Informed Multi-Modal Learning for Few-shot Novel View RIR Prediction
Chong Jing, Zitong Lan, Junan Zhang +1
Predicting spatially varying Room Impulse Response (RIR) from sparse observations is a critical but highly challenging inverse problem for immersive spatial audio rendering. In thi…