collaborators

5 papers

eess.AS2026

Diff-VS: Efficient Audio-Aware Diffusion U-Net for Vocals Separation

Yun-Ning, Hung, Richard Vogl +2

While diffusion models are best known for their performance in generative tasks, they have also been successfully applied to many other tasks, including audio source separation. Ho…

cs.SD2026

Timed text extraction from Taiwanese Kua-á-hì TV series

Tzu-Hung Huang, Yun-En Tsai, Yun-Ning Hung +3

Taiwanese opera (Kua-á-hì), a major form of local theatrical tradition, underwent extensive television adaptation notably by pioneers like Iûnn Lē-hua. These videos, while pote…

cs.SD2025

Generating Separated Singing Vocals Using a Diffusion Model Conditioned on Music Mixtures

Genís Plaja-Roglans, Yun-Ning Hung, Xavier Serra +1

Separating the individual elements in a musical mixture is an essential process for music analysis and practice. While this is generally addressed using neural networks optimized t…

cs.SD2025

Efficient and Fast Generative-Based Singing Voice Separation using a Latent Diffusion Model

Genís Plaja-Roglans, Yun-Ning Hung, Xavier Serra +1

Extracting individual elements from music mixtures is a valuable tool for music production and practice. While neural networks optimized to mask or transform mixture spectrograms i…

eess.AS2025

Moises-Light: Resource-efficient Band-split U-Net For Music Source Separation

Yun-Ning, Hung, Igor Pereira +1

In recent years, significant advances have been made in music source separation, with model architectures such as dual-path modeling, band-split modules, or transformer layers achi…