3 accepted papers
In multichannel speech enhancement, effectively capturing spatial and spectral information across different microphones is crucial for noise reduction. Traditional methods, such as CNN or LSTM, attempt to model the temporal dynamics of full-band and sub-band spectral and spatial features. However, t…
Surface electromyography (sEMG) recordings can be contaminated by electrocardiogram (ECG) signals when the monitored muscle is closed to the heart. Traditional signal processing-based approaches, such as high-pass filtering and template subtraction, have been used to remove ECG interference but are…
To improve noise robustness in automatic speech recognition (ASR), a common strategy is to employ speech enhancement (SE) models as front-ends for ASR systems. However, SE models often introduce artifacts into enhanced signals, which can degrade ASR performance, particularly when the SE and ASR mode…