111 citations · 781 across the 43 of their papers we have counts for
11 papers · 1 filter
A Unified Framework for Speech Separation
Fahimeh Bahmaninezhad, Shi-Xiong Zhang, Yong Xu +3
Speech separation refers to extracting each individual speech source in a given mixed signal. Recent advancements in speech separation and ongoing research in this area, have made…
Sound Event Detection of Weakly Labelled Data with CNN-Transformer and Automatic Threshold Optimization
Qiuqiang Kong, Yong Xu, Wenwu Wang +1
Sound event detection (SED) is a task to detect sound events in an audio recording. One challenge of the SED task is that many datasets such as the Detection and Classification of…
Audio-Visual Speech Separation and Dereverberation with a Two-Stage Multimodal Network
Ke Tan, Yong Xu, Shi-Xiong Zhang +2
Background noise, interfering speech and room reverberation frequently distort target speech in real listening environments. In this study, we address joint speech separation and d…
Single-Channel Signal Separation and Deconvolution with Generative Adversarial Networks
Qiuqiang Kong, Yong Xu, Wenwu Wang +2
Single-channel signal separation and deconvolution aims to separate and deconvolve individual sources from a single-channel mixture and is a challenging problem in which no prior k…
End-to-End Multi-Channel Speech Separation
Rongzhi Gu, Jian Wu, Shi-Xiong Zhang +6
The end-to-end approach for single-channel speech separation has been studied recently and shown promising results. This paper extended the previous approach and proposed a new end…
A comprehensive study of speech separation: spectrogram vs waveform separation
Fahimeh Bahmaninezhad, Jian Wu, Rongzhi Gu +4
Speech separation has been studied widely for single-channel close-talk microphone recordings over the past few years; developed solutions are mostly in frequency-domain. Recently,…
Cross-task learning for audio tagging, sound event detection spatial localization: DCASE 2019 baseline systems
Qiuqiang Kong, Yin Cao, Turab Iqbal +3
The Detection and Classification of Acoustic Scenes and Events (DCASE) 2019 challenge focuses on audio tagging, sound event detection and spatial localisation. DCASE 2019 consists…
Improved Speaker-Dependent Separation for CHiME-5 Challenge
Jian Wu, Yong Xu, Shi-Xiong Zhang +4
This paper summarizes several follow-up contributions for improving our submitted NWPU speaker-dependent system for CHiME-5 challenge, which aims to solve the problem of multi-chan…
Time Domain Audio Visual Speech Separation
Jian Wu, Yong Xu, Shi-Xiong Zhang +4
Audio-visual multi-modal modeling has been demonstrated to be effective in many speech related tasks, such as speech recognition and speech enhancement. This paper introduces a new…
Cross-task learning for audio tagging, sound event detection and spatial localization: DCASE 2019 baseline systems
Qiuqiang Kong, Yin Cao, Turab Iqbal +3
The Detection and Classification of Acoustic Scenes and Events (DCASE) 2019 challenge focuses on audio tagging, sound event detection and spatial localisation. DCASE 2019 consists…
Weakly Labelled AudioSet Tagging with Attention Neural Networks
Qiuqiang Kong, Changsong Yu, Turab Iqbal +3
Audio tagging is the task of predicting the presence or absence of sound classes within an audio clip. Previous work in audio tagging focused on relatively small datasets limited t…