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20222026
most citedSpeech Separation with Pretrained Frontend to Minimize Domain Mismatch

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

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5 papers · 1 filter

eess.AS2026

GigaSpeechBench: A Real-World Multilingual Speech-to-Text Benchmark

Yujie Tu, Yifan Yang, Tianrui Wang +35

While modern ASR systems achieve low error rates on high-resource benchmarks, such performance often overestimates real-world robustness. Existing evaluations address challenges in…

eess.AS2025

Leveraging Language Information for Target Language Extraction

Mehmet Sinan Yıldırım, Ruijie Tao, Wupeng Wang +2

Target Language Extraction aims to extract speech in a specific language from a mixture waveform that contains multiple speakers speaking different languages. The human auditory sy…

eess.AS2025

Online Audio-Visual Autoregressive Speaker Extraction

Zexu Pan, Wupeng Wang, Shengkui Zhao +4

This paper proposes a novel online audio-visual speaker extraction model. In the streaming regime, most studies optimize the audio network only, leaving the visual frontend less ex…

eess.AS2023

Selective HuBERT: Self-Supervised Pre-Training for Target Speaker in Clean and Mixture Speech

Jingru Lin, Meng Ge, Wupeng Wang +2

Self-supervised pre-trained speech models were shown effective for various downstream speech processing tasks. Since they are mainly pre-trained to map input speech to pseudo-label…

eess.AS2022

ImagineNET: Target Speaker Extraction with Intermittent Visual Cue through Embedding Inpainting

Zexu Pan, Wupeng Wang, Marvin Borsdorf +1

The speaker extraction technique seeks to single out the voice of a target speaker from the interfering voices in a speech mixture. Typically an auxiliary reference of the target s…