Jingzehua Xu

Imitating from auxiliary imperfect demonstrations via Adversarial Density Weighted Regression

2024 · arXiv (Cornell University)

We propose a novel one-step supervised imitation learning (IL) framework called Adversarial Density Regression (ADR). This IL framework aims to correct the policy learned on unknown-quality to match the expert distribution by utilizing demonstrations, without …

LHQ-SVC: Lightweight and High Quality Singing Voice Conversion Modeling

2024 · arXiv (Cornell University)

Singing Voice Conversion (SVC) has emerged as a significant subfield of Voice Conversion (VC), enabling the transformation of one singer's voice into another while preserving musical elements such as melody, rhythm, and timbre. Traditional SVC …