Papers by Chaofan Ding

1 papers
VocalRep: Structure-Aware Vocal Representations for Multimodal Generation (2026.findings-acl)

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Challenge: Existing approaches to vocal separation are optimized for signal-level reconstruction, but they overlook structural disentanglement required for downstream generation tasks.
Approach: They propose a structure-aware learning framework to disentangle vocals, harmonies, and accompaniment . they combine global vocal identity conditioning with ranking-based objectives .
Outcome: The proposed framework disentangles lead vocals, harmonies, and accompaniment while enforcing role consistency across long-form audio.

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