67 citations · 90 across the 13 of their papers we have counts for
13 papers
AutoPrep: An Automatic Preprocessing Framework for In-the-Wild Speech Data
Jianwei Yu, Hangting Chen, Yanyao Bian +6
Recently, the utilization of extensive open-sourced text data has significantly advanced the performance of text-based large language models (LLMs). However, the use of in-the-wild…
Bayes Risk Transducer: Transducer with Controllable Alignment Prediction
Jinchuan Tian, Jianwei Yu, Hangting Chen +4
Automatic speech recognition (ASR) based on transducers is widely used. In training, a transducer maximizes the summed posteriors of all paths. The path with the highest posterior…
Ultra Dual-Path Compression For Joint Echo Cancellation And Noise Suppression
Hangting Chen, Jianwei Yu, Yi Luo +4
Echo cancellation and noise reduction are essential for full-duplex communication, yet most existing neural networks have high computational costs and are inflexible in tuning mode…
High Fidelity Speech Enhancement with Band-split RNN
Jianwei Yu, Yi Luo, Hangting Chen +2
Despite the rapid progress in speech enhancement (SE) research, enhancing the quality of desired speech in environments with strong noise and interfering speakers remains challengi…
The HCCL System for the NIST SRE21
Zhuo Li, Runqiu Xiao, Hangting Chen +3
This paper describes the systems developed by the HCCL team for the NIST 2021 speaker recognition evaluation (NIST SRE21).We first explore various state-of-the-art speaker embeddin…
DPT-FSNet: Dual-path Transformer Based Full-band and Sub-band Fusion Network for Speech Enhancement
Feng Dang, Hangting Chen, Pengyuan Zhang
Sub-band models have achieved promising results due to their ability to model local patterns in the spectrogram. Some studies further improve the performance by fusing sub-band and…
Beam-Guided TasNet: An Iterative Speech Separation Framework with Multi-Channel Output
Hangting Chen, Yang Yi, Dang Feng +1
Time-domain audio separation network (TasNet) has achieved remarkable performance in blind source separation (BSS). Classic multi-channel speech processing framework employs signal…
Power pooling: An adaptive pooling function for weakly labelled sound event detection
Yuzhuo Liu, Hangting Chen, YunWang +1
Access to large corpora with strongly labelled sound events is expensive and difficult in engineering applications. Much research turns to address the problem of how to detect both…
Exploring the time-domain deep attractor network with two-stream architectures in a reverberant environment
Hangting Chen, Pengyuan Zhang
Deep attractor networks (DANs) perform speech separation with discriminative embeddings and speaker attractors. Compared with methods based on the permutation invariant training (P…
ACGAN-based Data Augmentation Integrated with Long-term Scalogram for Acoustic Scene Classification
Hangting Chen, Zuozhen Liu, Zongming Liu +1
In acoustic scene classification (ASC), acoustic features play a crucial role in the extraction of scene information, which can be stored over different time scales. Moreover, the…
Power Pooling Operators and Confidence Learning for Semi-Supervised Sound Event Detection
Yuzhuo Liu, Hangting Chen, Pengyuan Zhang
In recent years, the involvement of synthetic strongly labeled data,weakly labeled data and unlabeled data has drawn much research attentionin semi-supervised sound event detection…
Multi-Talker MVDR Beamforming Based on Extended Complex Gaussian Mixture Model
Hangting Chen, Pengyuan Zhang, Yonghong Yan
In this letter, we present a novel multi-talker minimum variance distortionless response (MVDR) beamforming as the front-end of an automatic speech recognition (ASR) system in a di…
Integrating the Data Augmentation Scheme with Various Classifiers for Acoustic Scene Modeling
Hangting Chen, Zuozhen Liu, Zongming Liu +2
This technical report describes the IOA team's submission for TASK1A of DCASE2019 challenge. Our acoustic scene classification (ASC) system adopts a data augmentation scheme employ…