From the 2 of 21 linked papers with an AI index.
10 papers · 1 filter
FlowSep 2: Self-Supervised Flow Matching for Language-Queried Audio Source Separation
Yi Yuan, Xubo Liu, Haohe Liu +3
Language-queried audio source separation (LASS) aims to extract target sources from audio mixtures according to natural language descriptions, offering a flexible and scalable inte…
Teaching Speech Enhancement Models to Sing: Domain Adaptation from Speech Enhancement to Singing Voice Separation
Paul A. Bereuter, Mark D. Plumbley, Alois Sontacchi
The paper adapts pretrained speech enhancement models to perform singing voice separation using fine‑tuning and low‑rank adaptation, achieving better separation with limited singin…
DreamAudio: Customized Text-to-Audio Generation with Diffusion Models
Yi Yuan, Xubo Liu, Haohe Liu +5
With the development of large-scale diffusion-based and language-modeling-based generative models, impressive progress has been achieved in text-to-audio generation. Despite produc…
AudioRAG+: Feedback-driven Retrieval-augmented Audio Generation with Large Audio Language Models
Junqi Zhao, Chenxing Li, Jinzheng Zhao +4
We propose a general feedback-driven retrieval-augmented generation (RAG) approach that leverages Large Audio Language Models (LALMs) to address the missing or imperfect synthesis…
Summary of The Inaugural Music Source Restoration Challenge
Yongyi Zang, Jiarui Hai, Wanying Ge +5
Music Source Restoration (MSR) aims to recover original, unprocessed instrument stems from professionally mixed and degraded audio, requiring the reversal of both production effect…
MSRBench: A Benchmarking Dataset for Music Source Restoration
Yongyi Zang, Jiarui Hai, Wanying Ge +5
Music Source Restoration (MSR) extends source separation to realistic settings where signals undergo production effects (equalization, compression, reverb) and real-world degradati…