2 citations · 7 across the 15 of their papers we have counts for
15 papers
Room Impulse Response as a Prompt for Acoustic Echo Cancellation
Fei Zhao, Shulin He, Xueliang Zhang
Data-driven acoustic echo cancellation (AEC) methods, predominantly trained on synthetic or constrained real-world datasets, encounter performance declines in unseen echo scenarios…
Listen to Extract: Onset-Prompted Target Speaker Extraction
Pengjie Shen, Kangrui Chen, Shulin He +5
We propose listen to extract (LExt), a highly-effective while extremely-simple algorithm for monaural target speaker extraction (TSE). Given an enrollment utterance of a target spe…
Robust Target Speaker Direction of Arrival Estimation
Zixuan Li, Shulin He, Xueliang Zhang
In multi-speaker environments the direction of arrival (DOA) of a target speaker is key for improving speech clarity and extracting target speaker's voice. However, traditional DOA…
SICRN: Advancing Speech Enhancement through State Space Model and Inplace Convolution Techniques
Changjiang Zhao, Shulin He, Xueliang Zhang
Speech enhancement aims to improve speech quality and intelligibility, especially in noisy environments where background noise degrades speech signals. Currently, deep learning met…
3S-TSE: Efficient Three-Stage Target Speaker Extraction for Real-Time and Low-Resource Applications
Shulin He, Jinjiang liu, Hao Li +3
Target speaker extraction (TSE) aims to isolate a specific voice from multiple mixed speakers relying on a registerd sample. Since voiceprint features usually vary greatly, current…
Hierarchical Modeling of Spatial Cues via Spherical Harmonics for Multi-Channel Speech Enhancement
Jiahui Pan, Shulin He, Hui Zhang +1
Multi-channel speech enhancement utilizes spatial information from multiple microphones to extract the target speech. However, most existing methods do not explicitly model spatial…
PDPCRN: Parallel Dual-Path CRN with Bi-directional Inter-Branch Interactions for Multi-Channel Speech Enhancement
Jiahui Pan, Shulin He, Tianci Wu +2
Multi-channel speech enhancement seeks to utilize spatial information to distinguish target speech from interfering signals. While deep learning approaches like the dual-path convo…
MC-SpEx: Towards Effective Speaker Extraction with Multi-Scale Interfusion and Conditional Speaker Modulation
Jun Chen, Wei Rao, Zilin Wang +5
The previous SpEx+ has yielded outstanding performance in speaker extraction and attracted much attention. However, it still encounters inadequate utilization of multi-scale inform…
Gesper: A Restoration-Enhancement Framework for General Speech Reconstruction
Wenzhe Liu, Yupeng Shi, Jun Chen +5
This paper describes a real-time General Speech Reconstruction (Gesper) system submitted to the ICASSP 2023 Speech Signal Improvement (SSI) Challenge. This novel proposed system is…
TEA-PSE 3.0: Tencent-Ethereal-Audio-Lab Personalized Speech Enhancement System For ICASSP 2023 DNS Challenge
Yukai Ju, Jun Chen, Shimin Zhang +6
This paper introduces the Unbeatable Team's submission to the ICASSP 2023 Deep Noise Suppression (DNS) Challenge. We expand our previous work, TEA-PSE, to its upgraded version -- T…
ExARN: self-attending RNN for target speaker extraction
Pengjie Shen, Shulin He, Xueliang Zhang
Target speaker extraction is to extract the target speaker, specified by enrollment utterance, in an environment with other competing speakers. Therefore, the task needs to solve t…
Speech Enhancement with Intelligent Neural Homomorphic Synthesis
Shulin He, Wei Rao, Jinjiang Liu +5
Most neural network speech enhancement models ignore speech production mathematical models by directly mapping Fourier transform spectrums or waveforms. In this work, we propose a…
Hierarchical speaker representation for target speaker extraction
Shulin He, Huaiwen Zhang, Wei Rao +4
Target speaker extraction aims to isolate a specific speaker's voice from a composite of multiple sound sources, guided by an enrollment utterance or called anchor. Current methods…
DBNet: A Dual-branch Network Architecture Processing on Spectrum and Waveform for Single-channel Speech Enhancement
Kanghao Zhang, Shulin He, Hao Li +1
In real acoustic environment, speech enhancement is an arduous task to improve the quality and intelligibility of speech interfered by background noise and reverberation. Over the…
Speakerfilter-Pro: an improved target speaker extractor combines the time domain and frequency domain
Shulin He, Hao Li, Xueliang Zhang
This paper introduces an improved target speaker extractor, referred to as Speakerfilter-Pro, based on our previous Speakerfilter model. The Speakerfilter uses a bi-direction gated…