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of 7
pro vyhledávání: '"Ju, Yukai"'
Autor:
Chen, Jun, Rao, Wei, Wang, Zilin, Lin, Jiuxin, Ju, Yukai, He, Shulin, Wang, Yannan, Wu, Zhiyong
The previous SpEx+ has yielded outstanding performance in speaker extraction and attracted much attention. However, it still encounters inadequate utilization of multi-scale information and speaker embedding. To this end, this paper proposes a new ef
Externí odkaz:
http://arxiv.org/abs/2306.16250
Autor:
Ju, Yukai, Chen, Jun, Zhang, Shimin, He, Shulin, Rao, Wei, Zhu, Weixin, Wang, Yannan, Yu, Tao, Shang, Shidong
This paper introduces the Unbeatable Team's submission to the ICASSP 2023 Deep Noise Suppression (DNS) Challenge. We expand our previous work, TEA-PSE, to its upgraded version -- TEA-PSE 3.0. Specifically, TEA-PSE 3.0 incorporates a residual LSTM aft
Externí odkaz:
http://arxiv.org/abs/2303.07704
This paper introduces the SWANT team entry to the ICASSP 2023 AEC Challenge. We submit a system that cascades a linear filter with a neural post-filter. Particularly, we adopt sub-band processing to handle full-band signals and shape the network with
Externí odkaz:
http://arxiv.org/abs/2303.06404
Autor:
He, Shulin, Rao, Wei, Liu, Jinjiang, Chen, Jun, Ju, Yukai, Zhang, Xueliang, Wang, Yannan, Shang, Shidong
Most neural network speech enhancement models ignore speech production mathematical models by directly mapping Fourier transform spectrums or waveforms. In this work, we propose a neural source filter network for speech enhancement. Specifically, we
Externí odkaz:
http://arxiv.org/abs/2210.15853
Target speaker extraction aims to isolate a specific speaker's voice from a composite of multiple sound sources, guided by an enrollment utterance or called anchor. Current methods predominantly derive speaker embeddings from the anchor and integrate
Externí odkaz:
http://arxiv.org/abs/2210.15849
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 interfering speech. In light of recent studies on personalized speech enhancem
Externí odkaz:
http://arxiv.org/abs/2205.15195
Autor:
He, Shulin, Rao, Wei, Zhang, Kanghao, Ju, Yukai, Yang, Yang, Zhang, Xueliang, Wang, Yannan, Shang, Shidong
Target speaker extraction is to extract the target speaker's voice from a mixture of signals according to the given enrollment utterance. The target speaker's enrollment utterance is also called as anchor speech. The effective utilization of anchor s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0f27096e7ca2f06d84f22ee4851b1b01
http://arxiv.org/abs/2210.15849
http://arxiv.org/abs/2210.15849