24 citations · 45 across the 17 of their papers we have counts for
6 papers · 1 filter
DasFormer: Deep Alternating Spectrogram Transformer for Multi/Single-Channel Speech Separation
Shuo Wang, Xiangyu Kong, Xiulian Peng +3
For the task of speech separation, previous study usually treats multi-channel and single-channel scenarios as two research tracks with specialized solutions developed respectively…
Contrast-PLC: Contrastive Learning for Packet Loss Concealment
Huaying Xue, Xiulian Peng, Yan Lu
Packet loss concealment (PLC) is challenging in concealing missing contents both plausibly and naturally when there are only limited available context to use. Recently deep-learnin…
Improving Speech Enhancement via Event-based Query
Yifei Xin, Xiulian Peng, Yan Lu
Existing deep learning based speech enhancement (SE) methods either use blind end-to-end training or explicitly incorporate speaker embedding or phonetic information into the SE ne…
Cross-Scale Vector Quantization for Scalable Neural Speech Coding
Xue Jiang, Xiulian Peng, Huaying Xue +2
Bitrate scalability is a desirable feature for audio coding in real-time communications. Existing neural audio codecs usually enforce a specific bitrate during training, so differe…
Multi-Modal Multi-Correlation Learning for Audio-Visual Speech Separation
Xiaoyu Wang, Xiangyu Kong, Xiulian Peng +1
In this paper we propose a multi-modal multi-correlation learning framework targeting at the task of audio-visual speech separation. Although previous efforts have been extensively…
Towards Error-Resilient Neural Speech Coding
Huaying Xue, Xiulian Peng, Xue Jiang +1
Neural audio coding has shown very promising results recently in the literature to largely outperform traditional codecs but limited attention has been paid on its error resilience…