1 citations · 2 across the 6 of their papers we have counts for
6 papers
MC-SpEx: Towards Effective Speaker Extraction with Multi-Scale Interfusion and Conditional Speaker Modulation
Jun Chen, Wei Rao, Zilin Wang +5
The previous SpEx+ has yielded outstanding performance in speaker extraction and attracted much attention. However, it still encounters inadequate utilization of multi-scale inform…
AV-SepFormer: Cross-Attention SepFormer for Audio-Visual Target Speaker Extraction
Jiuxin Lin, Xinyu Cai, Heinrich Dinkel +7
Visual information can serve as an effective cue for target speaker extraction (TSE) and is vital to improving extraction performance. In this paper, we propose AV-SepFormer, a Sep…
Gesper: A Restoration-Enhancement Framework for General Speech Reconstruction
Wenzhe Liu, Yupeng Shi, Jun Chen +5
This paper describes a real-time General Speech Reconstruction (Gesper) system submitted to the ICASSP 2023 Speech Signal Improvement (SSI) Challenge. This novel proposed system is…
Focus on the Sound around You: Monaural Target Speaker Extraction via Distance and Speaker Information
Jiuxin Lin, Peng Wang, Heinrich Dinkel +6
Previously, Target Speaker Extraction (TSE) has yielded outstanding performance in certain application scenarios for speech enhancement and source separation. However, obtaining au…
Inter-SubNet: Speech Enhancement with Subband Interaction
Jun Chen, Wei Rao, Zilin Wang +5
Subband-based approaches process subbands in parallel through the model with shared parameters to learn the commonality of local spectrums for noise reduction. In this way, they ha…
Speech Enhancement with Intelligent Neural Homomorphic Synthesis
Shulin He, Wei Rao, Jinjiang Liu +5
Most neural network speech enhancement models ignore speech production mathematical models by directly mapping Fourier transform spectrums or waveforms. In this work, we propose a…