4 papers
SSM2Mel: State Space Model to Reconstruct Mel Spectrogram from the EEG
Cunhang Fan, Sheng Zhang, Jingjing Zhang +2
Decoding speech from brain signals is a challenging research problem that holds significant importance for studying speech processing in the brain. Although breakthroughs have been…
Improved Feature Extraction Network for Neuro-Oriented Target Speaker Extraction
Cunhang Fan, Youdian Gao, Zexu Pan +4
The recent rapid development of auditory attention decoding (AAD) offers the possibility of using electroencephalography (EEG) as auxiliary information for target speaker extractio…
BSDB-Net: Band-Split Dual-Branch Network with Selective State Spaces Mechanism for Monaural Speech Enhancement
Cunhang Fan, Enrui Liu, Andong Li +5
Although the complex spectrum-based speech enhancement(SE) methods have achieved significant performance, coupling amplitude and phase can lead to a compensation effect, where ampl…
LiSenNet: Lightweight Sub-band and Dual-Path Modeling for Real-Time Speech Enhancement
Haoyin Yan, Jie Zhang, Cunhang Fan +2
Speech enhancement (SE) aims to extract the clean waveform from noise-contaminated measurements to improve the speech quality and intelligibility. Although learning-based methods c…