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From the 1 of 9 linked papers with an AI index.

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9 papers

cs.SD2026

Diff-Symbo: Text-Controlled Long-Duration Symbolic Music Generation Using Autoregressive Latent Diffusion Model

Zhiwei Lin, Jun Chen, Boshi Tang +5

Text-controlled symbolic music generation has recently gained research attention due to its versatile, flexible and straightforward approach to music composition. However, previous…

cs.SD2026

P-MUSE: Prompt-MIDI-Optional Model for Unified Instrumental Music Synthesis and Editing

Chong Jing, Junan Zhang, Jing Yang +3

MIDI-to-Music system renders the melody and rhythm of a target MIDI sequence into musical segment while cloning instrument timbre from a prompt recording. Existing systems typicall…

cs.SD2026

Anysynth:Zero-Shot Instrument Cloning via In-Context Learning and Asymmetric Hierarchical Guidance

Chong Jing, Junan Zhang, Jing Yang +3

The paper presents Anysynth, a diffusion‑transformer synthesizer that can render arbitrary target MIDI sequences with the timbre of an unseen instrument by directly conditioning on…

cs.SD2026

Schrödinger Bridge Mamba for One-Step Speech Enhancement

Jing Yang, Sirui Wang, Chao Wu +2

We present Schrödinger Bridge Mamba (SBM), a novel model for efficient speech enhancement by integrating the Schrödinger Bridge (SB) training paradigm and the Mamba architecture.…

cs.SD2025

Multi-Metric Preference Alignment for Generative Speech Restoration

Junan Zhang, Xueyao Zhang, Jing Yang +3

Recent generative models have significantly advanced speech restoration tasks, yet their training objectives often misalign with human perceptual preferences, resulting in suboptim…

cs.SD2025

AnyEnhance: A Unified Generative Model with Prompt-Guidance and Self-Critic for Voice Enhancement

Junan Zhang, Jing Yang, Zihao Fang +5

We introduce AnyEnhance, a unified generative model for voice enhancement that processes both speech and singing voices. Based on a masked generative model, AnyEnhance is capable o…