8 papers
Is One Score Enough? Assessing Singing Quality of Songs with Temporal Score Curves
Yishan Lv, Jing Luo, Xinyu Yang +1
Singing Quality Assessment (SQA) has become increasingly important for practical multimedia applications and Music AI systems, yet existing studies predominantly focus on short sin…
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…
Zero-VC: Zero-Lookahead Streaming Voice Conversion via Speaker Anonymization
Yudong Li, Zihao Fang, Junwen Qiu +4
Streaming zero-shot voice conversion struggles to disentangle timbre from linguistic content without degrading utility or inflating latency. Current methods rely on information bot…
Neurodyne: Neural Pitch Manipulation with Representation Learning and Cycle-Consistency GAN
Yicheng Gu, Chaoren Wang, Zhizheng Wu +1
Pitch manipulation is the process of producers adjusting the pitch of an audio segment to a specific key and intonation, which is essential in music production. Neural-network-base…
Solid State Bus-Comp: A Large-Scale and Diverse Dataset for Dynamic Range Compressor Virtual Analog Modeling
Yicheng Gu, Runsong Zhang, Lauri Juvela +1
Virtual Analog (VA) modeling aims to simulate the behavior of hardware circuits via algorithms to replicate their tone digitally. Dynamic Range Compressor (DRC) is an audio process…
SingNet: Towards a Large-Scale, Diverse, and In-the-Wild Singing Voice Dataset
Yicheng Gu, Chaoren Wang, Junan Zhang +4
The lack of a publicly-available large-scale and diverse dataset has long been a significant bottleneck for singing voice applications like Singing Voice Synthesis (SVS) and Singin…