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20232026
most citedSpeech Separation with Pretrained Frontend to Minimize Domain Mismatch

11 citations · 12 across the 24 of their papers we have counts for

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eess.AS2026

WeSep: A Modular and Cue-Composable Framework for Target Speaker Extraction

Ke Zhang, Xiaoyang Yu, Haoyu Li +3

The study of Target Speaker Extraction (TSE) aims to isolate a desired speaker from overlapping speech mixture given auxiliary cues. Existing systems are typically designed for spe…

eess.AS2026

SLT 2026 REAL-TSE Challenge: Real-world Target Speaker Extraction from Conversational Recordings

Shuai Wang, Zihan Qian, Ke Zhang +9

We introduce the REAL-TSE Challenge, an IEEE SLT 2026 satellite challenge on target speaker extraction~(TSE) from real conversational recordings. Given a multi-speaker mixture and…

eess.AS2026

Detect, Attend and Extract: Keyword Guided Target Speaker Extraction

Haoyu Li, Yu Xi, Yidi Jiang +5

Target speaker extraction (TSE) aims to extract the speech of a target speaker from mixtures containing multiple competing speakers. Conventional TSE systems predominantly rely on…

eess.AS2025

Direct Preference Optimization for Speech Autoregressive Diffusion Models

Zhijun Liu, Dongya Jia, Xiaoqiang Wang +4

Autoregressive diffusion models (ARDMs) have recently been applied to speech generation, achieving state-of-the-art (SOTA) performance in zero-shot text-to-speech. By autoregressiv…

eess.AS2025

Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data

Qibing Bai, Sho Inoue, Shuai Wang +3

Accent normalization converts foreign-accented speech into native-like speech while preserving speaker identity. We propose a novel pipeline using self-supervised discrete tokens a…

eess.AS2025

SpeechRefiner: Towards Perceptual Quality Refinement for Front-End Algorithms

Sirui Li, Shuai Wang, Zhijun Liu +3

Speech pre-processing techniques such as denoising, de-reverberation, and separation, are commonly employed as front-ends for various downstream speech processing tasks. However, t…