137 citations · 201 across the 19 of their papers we have counts for
11 papers · 1 filter
Masked Audio Modeling with CLAP and Multi-Objective Learning
Yifei Xin, Xiulian Peng, Yan Lu
Most existing masked audio modeling (MAM) methods learn audio representations by masking and reconstructing local spectrogram patches. However, the reconstruction loss mainly accou…
Low-latency Speech Enhancement via Speech Token Generation
Huaying Xue, Xiulian Peng, Yan Lu
Existing deep learning based speech enhancement mainly employ a data-driven approach, which leverage large amounts of data with a variety of noise types to achieve noise removal fr…
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…
Disentangled Feature Learning for Real-Time Neural Speech Coding
Xue Jiang, Xiulian Peng, Yuan Zhang +1
Recently end-to-end neural audio/speech coding has shown its great potential to outperform traditional signal analysis based audio codecs. This is mostly achieved by following the…
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…
Latent-Domain Predictive Neural Speech Coding
Xue Jiang, Xiulian Peng, Huaying Xue +2
Neural audio/speech coding has recently demonstrated its capability to deliver high quality at much lower bitrates than traditional methods. However, existing neural audio/speech c…
End-to-End Neural Speech Coding for Real-Time Communications
Xue Jiang, Xiulian Peng, Chengyu Zheng +3
Deep-learning based methods have shown their advantages in audio coding over traditional ones but limited attention has been paid on real-time communications (RTC). This paper prop…