8 citations · 9 across the 16 of their papers we have counts for
4 papers · 1 filter
The ISCSLP 2026 Real-World Audio-Visual Speech Enhancement Challenge: A Benchmark with Natural Mixtures and Degraded Video
Kai Li, Wenze Ren, Junjie Li +11
Audio-visual speech enhancement (AVSE) uses a target speaker's visible articulation to recover that speaker's voice from overlapped speech. Yet most evaluation protocols rely on sy…
A Knowledge-Driven Approach to Target Speech Extraction in the Presence of Background Sound Effects for Cinematic Audio Source Separation (CASS)
Chun-wei Ho, Sabato Marco Siniscalchi, Kai Li +1
We propose a knowledge-driven approach to speech target extraction in the presence of background sound effects already recorded in cinematic audio. The specific knowledge sources s…
Unsupervised Single-Channel Speech Separation with Diffusion under Speaker-Embedding Guidance
Runwu Shi, Kai Li, Yiyan Wang +5
Speech separation is a fundamental task in audio processing, typically addressed with fully supervised systems trained on paired mixtures. While effective, such systems typically r…
SoloSpeech: Enhancing Intelligibility and Quality in Target Speech Extraction through a Cascaded Generative Pipeline
Helin Wang, Jiarui Hai, Dongchao Yang +7
Target Speech Extraction (TSE) aims to isolate a target speaker's voice from a mixture of multiple speakers by leveraging speaker-specific cues, typically provided as auxiliary aud…