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20242026
most citedDiffusion-based Signal Refiner for Speech Enhancement and Separation

1 citations · 1 across the 11 of their papers we have counts for

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cs.SD2025

SteerMusic: Enhanced Musical Consistency for Zero-shot Text-guided and Personalized Music Editing

Xinlei Niu, Kin Wai Cheuk, Jing Zhang +8

Music editing is an important step in music production, which has broad applications, including game development and film production. Most existing zero-shot text-guided editing me…

cs.SD2025

Large-Scale Training Data Attribution for Music Generative Models via Unlearning

Woosung Choi, Junghyun Koo, Kin Wai Cheuk +7

This paper explores the use of unlearning methods for training data attribution (TDA) in music generative models trained on large-scale datasets. TDA aims to identify which specifi…

cs.SD2025

Instruct-MusicGen: Unlocking Text-to-Music Editing for Music Language Models via Instruction Tuning

Yixiao Zhang, Yukara Ikemiya, Woosung Choi +7

Recent advances in text-to-music editing, which employ text queries to modify music (e.g.\ by changing its style or adjusting instrumental components), present unique challenges an…

cs.SD2025

Schrödinger Bridge Consistency Trajectory Models for Speech Enhancement

Shuichiro Nishigori, Koichi Saito, Naoki Murata +3

Speech enhancement (SE) utilizing diffusion models is a promising technology that improves speech quality in noisy speech data. Furthermore, the Schrödinger bridge (SB) has recent…

cs.SD2024

MusicMagus: Zero-Shot Text-to-Music Editing via Diffusion Models

Yixiao Zhang, Yukara Ikemiya, Gus Xia +5

Recent advances in text-to-music generation models have opened new avenues in musical creativity. However, music generation usually involves iterative refinements, and how to edit…