62 citations · 142 across the 15 of their papers we have counts for
15 papers
CabinSep: IR-Augmented Mask-Based MVDR for Real-Time In-Car Speech Separation with Distributed Heterogeneous Arrays
Runduo Han, Yanxin Hu, Yihui Fu +4
Separating overlapping speech from multiple speakers is crucial for effective human-vehicle interaction. This paper proposes CabinSep, a lightweight neural mask-based minimum varia…
VE-KWS: Visual Modality Enhanced End-to-End Keyword Spotting
Ao Zhang, He Wang, Pengcheng Guo +5
The performance of the keyword spotting (KWS) system based on audio modality, commonly measured in false alarms and false rejects, degrades significantly under the far field and no…
spatial-dccrn: dccrn equipped with frame-level angle feature and hybrid filtering for multi-channel speech enhancement
Shubo Lv, Yihui Fu, Yukai Jv +4
Recently, multi-channel speech enhancement has drawn much interest due to the use of spatial information to distinguish target speech from interfering signal. To make full use of s…
Personalized Acoustic Echo Cancellation for Full-duplex Communications
Shimin Zhang, Ziteng Wang, Yukai Ju +4
Deep neural networks (DNNs) have shown promising results for acoustic echo cancellation (AEC). But the DNN-based AEC models let through all near-end speakers including the interfer…
Summary On The ICASSP 2022 Multi-Channel Multi-Party Meeting Transcription Grand Challenge
Fan Yu, Shiliang Zhang, Pengcheng Guo +13
The ICASSP 2022 Multi-channel Multi-party Meeting Transcription Grand Challenge (M2MeT) focuses on one of the most valuable and the most challenging scenarios of speech technologie…
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…
Uformer: A Unet based dilated complex & real dual-path conformer network for simultaneous speech enhancement and dereverberation
Yihui Fu, Yun Liu, Jingdong Li +4
Complex spectrum and magnitude are considered as two major features of speech enhancement and dereverberation. Traditional approaches always treat these two features separately, ig…
M2MeT: The ICASSP 2022 Multi-Channel Multi-Party Meeting Transcription Challenge
Fan Yu, Shiliang Zhang, Yihui Fu +9
Recent development of speech processing, such as speech recognition, speaker diarization, etc., has inspired numerous applications of speech technologies. The meeting scenario is o…
INTERSPEECH 2021 ConferencingSpeech Challenge: Towards Far-field Multi-Channel Speech Enhancement for Video Conferencing
Wei Rao, Yihui Fu, Yanxin Hu +11
The ConferencingSpeech 2021 challenge is proposed to stimulate research on far-field multi-channel speech enhancement for video conferencing. The challenge consists of two separate…
AISHELL-4: An Open Source Dataset for Speech Enhancement, Separation, Recognition and Speaker Diarization in Conference Scenario
Yihui Fu, Luyao Cheng, Shubo Lv +10
In this paper, we present AISHELL-4, a sizable real-recorded Mandarin speech dataset collected by 8-channel circular microphone array for speech processing in conference scenario.…
The NPU System for the 2020 Personalized Voice Trigger Challenge
Jingyong Hou, Li Zhang, Yihui Fu +4
This paper describes the system developed by the NPU team for the 2020 personalized voice trigger challenge. Our submitted system consists of two independently trained subsystems:…
IEEE SLT 2021 Alpha-mini Speech Challenge: Open Datasets, Tracks, Rules and Baselines
Yihui Fu, Zhuoyuan Yao, Weipeng He +9
The IEEE Spoken Language Technology Workshop (SLT) 2021 Alpha-mini Speech Challenge (ASC) is intended to improve research on keyword spotting (KWS) and sound source location (SSL)…
DESNet: A Multi-channel Network for Simultaneous Speech Dereverberation, Enhancement and Separation
Yihui Fu, Jian Wu, Yanxin Hu +2
In this paper, we propose a multi-channel network for simultaneous speech dereverberation, enhancement and separation (DESNet). To enable gradient propagation and joint optimizatio…
DCCRN: Deep Complex Convolution Recurrent Network for Phase-Aware Speech Enhancement
Yanxin Hu, Yun Liu, Shubo Lv +6
Speech enhancement has benefited from the success of deep learning in terms of intelligibility and perceptual quality. Conventional time-frequency (TF) domain methods focus on pred…