23 citations · 29 across the 7 of their papers we have counts for
7 papers
Convert and Speak: Zero-shot Accent Conversion with Minimum Supervision
Zhijun Jia, Huaying Xue, Xiulian Peng +1
Low resource of parallel data is the key challenge of accent conversion(AC) problem in which both the pronunciation units and prosody pattern need to be converted. We propose a two…
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…
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…
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…
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…