4 papers
Benchmarking Neural Speech Compression from a Rate-Distortion Perspective
Jun Xu, Zhengxue Cheng, Fengxi Zhang +3
Learning-based speech compression has achieved promising low-bitrate performance, but many neural speech codecs still describe quantized latents with preset-rate discrete symbols o…
MeetBench-XL: Calibrated Multi-Dimensional Evaluation and Learned Dual-Policy Agents for Real-Time Meetings
Yuelin Hu, Jun Xu, Bingcong Lu +4
Enterprise meeting environments require AI assistants that handle diverse operational tasks, from rapid fact checking during live discussions to cross meeting analysis for strategi…
Lightweight High-Fidelity Low-Bitrate Talking Face Compression for 3D Video Conference
Jianglong Li, Jun Xu, Bingcong Lu +4
The demand for immersive and interactive communication has driven advancements in 3D video conferencing, yet achieving high-fidelity 3D talking face representation at low bitrates…
Rate-Aware Learned Speech Compression
Jun Xu, Zhengxue Cheng, Guangchuan Chi +3
The rapid rise of real-time communication and large language models has significantly increased the importance of speech compression. Deep learning-based neural speech codecs have…