111 citations · 412 across the 36 of their papers we have counts for
5 papers · 1 filter
Improving Dual-Microphone Speech Enhancement by Learning Cross-Channel Features with Multi-Head Attention
Xinmeng Xu, Rongzhi Gu, Yuexian Zou
Hand-crafted spatial features, such as inter-channel intensity difference (IID) and inter-channel phase difference (IPD), play a fundamental role in recent deep learning based dual…
SpecAugment++: A Hidden Space Data Augmentation Method for Acoustic Scene Classification
Helin Wang, Yuexian Zou, Wenwu Wang
In this paper, we present SpecAugment++, a novel data augmentation method for deep neural networks based acoustic scene classification (ASC). Different from other popular data augm…
A Global-local Attention Framework for Weakly Labelled Audio Tagging
Helin Wang, Yuexian Zou, Wenwu Wang
Weakly labelled audio tagging aims to predict the classes of sound events within an audio clip, where the onset and offset times of the sound events are not provided. Previous work…
Enhancing End-to-End Multi-channel Speech Separation via Spatial Feature Learning
Rongzhi Gu, Shi-Xiong Zhang, Lianwu Chen +5
Hand-crafted spatial features (e.g., inter-channel phase difference, IPD) play a fundamental role in recent deep learning based multi-channel speech separation (MCSS) methods. Howe…
Multi-modal Multi-channel Target Speech Separation
Rongzhi Gu, Shi-Xiong Zhang, Yong Xu +3
Target speech separation refers to extracting a target speaker's voice from an overlapped audio of simultaneous talkers. Previously the use of visual modality for target speech sep…