EEG artifact removal—state-of-the-art and guidelines
This paper presents an extensive review on the artifact removal algorithms used to remove
the main sources of interference encountered in the electroencephalogram (EEG) …
the main sources of interference encountered in the electroencephalogram (EEG) …
Artifact removal in physiological signals—Practices and possibilities
The combination of reducing birth rate and increasing life expectancy continues to drive the
demographic shift toward an aging population. This, in turn, places an ever-increasing …
demographic shift toward an aging population. This, in turn, places an ever-increasing …
Conv-tasnet: Surpassing ideal time–frequency magnitude masking for speech separation
Single-channel, speaker-independent speech separation methods have recently seen great
progress. However, the accuracy, latency, and computational cost of such methods remain …
progress. However, the accuracy, latency, and computational cost of such methods remain …
A survey on audio diffusion models: Text to speech synthesis and enhancement in generative ai
Generative AI has demonstrated impressive performance in various fields, among which
speech synthesis is an interesting direction. With the diffusion model as the most popular …
speech synthesis is an interesting direction. With the diffusion model as the most popular …
Voice separation with an unknown number of multiple speakers
We present a new method for separating a mixed audio sequence, in which multiple voices
speak simultaneously. The new method employs gated neural networks that are trained to …
speak simultaneously. The new method employs gated neural networks that are trained to …
A block coordinate descent method for regularized multiconvex optimization with applications to nonnegative tensor factorization and completion
This paper considers regularized block multiconvex optimization, where the feasible set and
objective function are generally nonconvex but convex in each block of variables. It also …
objective function are generally nonconvex but convex in each block of variables. It also …
Speaker-independent speech separation with deep attractor network
Despite the recent success of deep learning for many speech processing tasks, single-
microphone, speaker-independent speech separation remains challenging for two main …
microphone, speaker-independent speech separation remains challenging for two main …
Automatic classification of artifactual ICA-components for artifact removal in EEG signals
Background Artifacts contained in EEG recordings hamper both, the visual interpretation by
experts as well as the algorithmic processing and analysis (eg for Brain-Computer Interfaces …
experts as well as the algorithmic processing and analysis (eg for Brain-Computer Interfaces …
Extracting multi-person respiration from entangled RF signals
Recent advances in wireless systems have demonstrated the possibility of tracking a
person's respiration using the RF signals that bounce off her body. The resulting breathing …
person's respiration using the RF signals that bounce off her body. The resulting breathing …
Robust artifactual independent component classification for BCI practitioners
Objective. EEG artifacts of non-neural origin can be separated from neural signals by
independent component analysis (ICA). It is unclear (1) how robustly recently proposed …
independent component analysis (ICA). It is unclear (1) how robustly recently proposed …