5 papers
Neuromorphic Speech Enhancement with Dual-Branch Spiking Neural Networks
Taiyu Meng, Wenbin Jiang, Haoyi Zhang +2
Spiking neural network (SNN)-based neuromorphic speech enhancement has emerged as a promising paradigm due to its energy efficiency, yet it still underperforms classical artificial…
Time-Unconditional Generative Speech Enhancement via Autonomous Rectified Flow
Wen Zhang, Wenbin Jiang, Yang Zhang +1
Most generative speech enhancement methods rely on explicit time-step embeddings for temporal conditioning. In this paper, we propose the Autonomous Rectified Flow framework, which…
KFC-KWS: Keyframe Fusion with CTC for User-Defined Keyword Spotting
Jin Li, Wenbin Jiang, Ji Hu
User-defined keyword spotting (KWS) enables personalized voice interaction by detecting user-specified keywords. A key challenge in this task is distinguishing target keywords from…
Switchcodec: Adaptive residual-expert sparse quantization for high-fidelity neural audio coding
Xiangbo Wang, Wenbin Jiang, Jin Wang +3
Recent neural audio compression models often rely on residual vector quantization for high-fidelity coding, but using a fixed number of per-frame codebooks is suboptimal for the wi…
SwitchCodec: A High-Fidelity Nerual Audio Codec With Sparse Quantization
Jin Wang, Wenbin Jiang, Xiangbo Wang +2
Neural audio compression has emerged as a promising technology for efficiently representing speech, music, and general audio. However, existing methods suffer from significant perf…