6 citations · 8 across the 16 of their papers we have counts for
5 papers · 1 filter
UNITE-AUDIO: Joint Learning of Continuous Tokenization and Latent Flow Matching for Text-to-Audio Generation
Runwu Shi, Kai Li, Yujin Wang +8
Text-to-audio (TTA) generation aims to synthesize realistic audio that faithfully reflects natural-language descriptions. Most TTA systems adopt a two-stage latent paradigm: an aud…
Exploring Efficient Waveform Diffusion Models for Foley Sound Generation
Runwu Shi, Chang Li, Jiahui Li +7
Recent advances in diffusion models have enabled high-fidelity Foley sound generation directly in the waveform space. Existing waveform diffusion models primarily rely on time-doma…
Unsupervised Single-Channel Audio Separation with Diffusion Source Priors
Runwu Shi, Chang Li, Jiang Wang +5
Single-channel audio separation aims to separate individual sources from a single-channel mixture. Most existing methods rely on supervised learning with synthetically generated pa…
Single-Channel Target Speech Extraction Utilizing Distance and Room Clues
Runwu Shi, Zirui Lin, Benjamin Yen +3
This paper aims to achieve single-channel target speech extraction (TSE) in enclosures utilizing distance clues and room information. Recent works have verified the feasibility of…
Distance Based Single-Channel Target Speech Extraction
Runwu Shi, Benjamin Yen, Kazuhiro Nakadai
This paper aims to achieve single-channel target speech extraction (TSE) in enclosures by solely utilizing distance information. This is the first work that utilizes only distance…