5 papers
Adaptive Depth and Expert Refinement for Efficient Speech Enhancement
Xikun Lu, Yujian Ma, Yunda Chen +2
Most neural speech enhancement systems use a fixed processing depth for all inputs, which can introduce unnecessary computation when fewer refinement steps are sufficient. We propo…
Consensus-Guided Shared-Specific Tri-View Learning for Speech Emotion Recognition
Bing Huang, Yujian Ma, Xikun Lu +2
Speech emotion recognition (SER) benefits from heterogeneous acoustic representations, but views derived from the same utterance contain both overlapping emotional evidence and rep…
From Semantics to Readout: Mechanistic Understanding of Audio Tokens after Fine-Tuning for Temporal Audio Grounding
Yujian Ma, Jinqiu Sang, Ruizhe Li +2
Large audio-language models (LALMs) convey acoustic evidence to language decoders through native audio tokens, yet the internal roles of these tokens remain poorly understood. Usin…
A Lightweight Fourier-based Network for Binaural Speech Enhancement with Spatial Cue Preservation
Xikun Lu, Yujian Ma, Xianquan Jiang +2
Binaural speech enhancement faces a severe trade-off challenge, where state-of-the-art performance is achieved by computationally intensive architectures, while lightweight solutio…
Lightweight Implicit Neural Network for Binaural Audio Synthesis
Xikun Lu, Fang Liu, Weizhi Shi +1
High-fidelity binaural audio synthesis is crucial for immersive listening, but existing methods require extensive computational resources, limiting their edge-device application. T…