29 citations · 44 across the 9 of their papers we have counts for
9 papers
DualSep: A Light-weight dual-encoder convolutional recurrent network for real-time in-car speech separation
Ziqian Wang, Jiayao Sun, Zihan Zhang +3
Advancements in deep learning and voice-activated technologies have driven the development of human-vehicle interaction. Distributed microphone arrays are widely used in in-car sce…
ICMC-ASR: The ICASSP 2024 In-Car Multi-Channel Automatic Speech Recognition Challenge
He Wang, Pengcheng Guo, Yue Li +13
To promote speech processing and recognition research in driving scenarios, we build on the success of the Intelligent Cockpit Speech Recognition Challenge (ICSRC) held at ISCSLP 2…
BS-PLCNet: Band-split Packet Loss Concealment Network with Multi-task Learning Framework and Multi-discriminators
Zihan Zhang, Jiayao Sun, Xianjun Xia +3
Packet loss is a common and unavoidable problem in voice over internet phone (VoIP) systems. To deal with the problem, we propose a band-split packet loss concealment network (BS-P…
An audio-quality-based multi-strategy approach for target speaker extraction in the MISP 2023 Challenge
Runduo Han, Xiaopeng Yan, Weiming Xu +6
This paper describes our audio-quality-based multi-strategy approach for the audio-visual target speaker extraction (AVTSE) task in the Multi-modal Information based Speech Process…
An Exploration of Task-decoupling on Two-stage Neural Post Filter for Real-time Personalized Acoustic Echo Cancellation
Zihan Zhang, Jiayao Sun, Xianjun Xia +4
Deep learning based techniques have been popularly adopted in acoustic echo cancellation (AEC). Utilization of speaker representation has extended the frontier of AEC, thus attract…
Multi-Task Sub-Band Network For Deep Residual Echo Suppression
Jiayao Sun, Dawei Luo, Zhaoxia Li +3
This paper introduces the SWANT team entry to the ICASSP 2023 AEC Challenge. We submit a system that cascades a linear filter with a neural post-filter. Particularly, we adopt sub-…
Multi-Task Deep Residual Echo Suppression with Echo-aware Loss
Shimin Zhang, Ziteng Wang, Jiayao Sun +4
This paper introduces the NWPU Team's entry to the ICASSP 2022 AEC Challenge. We take a hybrid approach that cascades a linear AEC with a neural post-filter. The former is used to…
S-DCCRN: Super Wide Band DCCRN with learnable complex feature for speech enhancement
Shubo Lv, Yihui Fu, Mengtao Xing +5
In speech enhancement, complex neural network has shown promising performance due to their effectiveness in processing complex-valued spectrum. Most of the recent speech enhancemen…
A Two-stream End-to-End Deep Learning Network for Recognizing Atypical Visual Attention in Autism Spectrum Disorder
Jin Xie, Longfei Wang, Paula Webster +4
Eye movements have been widely investigated to study the atypical visual attention in Autism Spectrum Disorder (ASD). The majority of these studies have been focused on limited eye…