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cs.SD2025

DAFMSVC: One-Shot Singing Voice Conversion with Dual Attention Mechanism and Flow Matching

Wei Chen, Binzhu Sha, Dan Luo +4

Singing Voice Conversion (SVC) transfers a source singer's timbre to a target while keeping melody and lyrics. The key challenge in any-to-any SVC is adapting unseen speaker timbre…

cs.SD2025

Singing Voice Conversion with Accompaniment Using Self-Supervised Representation-Based Melody Features

Wei Chen, Binzhu Sha, Jing Yang +3

Melody preservation is crucial in singing voice conversion (SVC). However, in many scenarios, audio is often accompanied with background music (BGM), which can cause audio distorti…

cs.SD2024

RobustSVC: HuBERT-based Melody Extractor and Adversarial Learning for Robust Singing Voice Conversion

Wei Chen, Xintao Zhao, Jun Chen +3

Singing voice conversion (SVC) is hindered by noise sensitivity due to the use of non-robust methods for extracting pitch and energy during the inference. As clean signals are key…

cs.SD2024

Multi-view MidiVAE: Fusing Track- and Bar-view Representations for Long Multi-track Symbolic Music Generation

Zhiwei Lin, Jun Chen, Boshi Tang +7

Variational Autoencoders (VAEs) constitute a crucial component of neural symbolic music generation, among which some works have yielded outstanding results and attracted considerab…

cs.SD2024

Neural Concatenative Singing Voice Conversion: Rethinking Concatenation-Based Approach for One-Shot Singing Voice Conversion

Binzhu Sha, Xu Li, Zhiyong Wu +2

Any-to-any singing voice conversion (SVC) is confronted with the challenge of ``timbre leakage'' issue caused by inadequate disentanglement between the content and the speaker timb…