111 citations · 412 across the 36 of their papers we have counts for
6 papers · 1 filter
Unsupervised Multi-Target Domain Adaptation for Acoustic Scene Classification
Dongchao Yang, Helin Wang, Yuexian Zou
It is well known that the mismatch between training (source) and test (target) data distribution will significantly decrease the performance of acoustic scene classification (ASC)…
Complex Neural Spatial Filter: Enhancing Multi-channel Target Speech Separation in Complex Domain
Rongzhi Gu, Shi-Xiong Zhang, Yuexian Zou +1
To date, mainstream target speech separation (TSS) approaches are formulated to estimate the complex ratio mask (cRM) of the target speech in time-frequency domain under supervised…
Acoustic Scene Classification with Spectrogram Processing Strategies
Helin Wang, Yuexian Zou, Dading Chong
Recently, convolutional neural networks (CNN) have achieved the state-of-the-art performance in acoustic scene classification (ASC) task. The audio data is often transformed into t…
Temporal-Spatial Neural Filter: Direction Informed End-to-End Multi-channel Target Speech Separation
Rongzhi Gu, Yuexian Zou
Target speech separation refers to extracting the target speaker's speech from mixed signals. Despite the recent advances in deep learning based close-talk speech separation, the a…
Environmental Sound Classification with Parallel Temporal-spectral Attention
Helin Wang, Yuexian Zou, Dading Chong +1
Convolutional neural networks (CNN) are one of the best-performing neural network architectures for environmental sound classification (ESC). Recently, temporal attention mechanism…
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…