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Single-Channel Blind Source Separation using Adaptive Mode Separation-Based Wavelet Transform and Density-Based Clustering with Sparse Reconstruction
In this paper, the problem of single-channel blind source separation (SCBSS) is addressed using a novel approach that combines the adaptive mode...
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A smart universal single-channel blind source separation method and applications
In industrial, biological, medical and many more scenarios, single-channel blind source separation still remains challenges. A smart universal...
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A Single-Channel Blind Separation Convolutional Network Combined with Attention Mechanism for Communication Signals
With the rapid development of information transfer technology and the influence of complex electromagnetic environment, the signal components in...
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An Investigation into Noise Source Separation and Blind Identification Method for Electric Drive System Based on Single-Channel Noise Sources
During the analysis of noise source characteristics in electric vehicles, signal processing methods are required for the noise excitation source of...
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Single channel source separation using time–frequency non-negative matrix factorization and sigmoid base normalization deep neural networks
Conventional single channel speech separation has two long-standing issues. The first issue, over-smoothing, is addressed, and estimated signals are...
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Time-domain adaptive attention network for single-channel speech separation
Recent years have witnessed a great progress in single-channel speech separation by applying self-attention based networks. Despite the excellent...
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Predominant audio source separation in polyphonic music
Predominant source separation is the separation of one or more desired predominant signals, such as voice or leading instruments, from polyphonic...
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Single-channel blind source separation based on attentional generative adversarial network
Blind single-channel source separation is a long-standing machine learning and signal processing problem. Traditional blind source separation (BSS)...
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Source separation from single-channel abdominal phonocardiographic signals based on independent component analysis
Purpose : Continuous monitoring of fetal heart rate (FHR) is essential to diagnose heart abnormalities. Therefore, FHR measurement is considered as...
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Underdetermined Blind Source Separation Based on Spatial Estimation and Compressed Sensing
This paper proposes a dual-channel speech separation method based on spatial estimation via sparse Bayesian inference (SBI) and nonnegative matrix...
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Exploring single channel speech separation for short-time text-dependent speaker verification
The automatic speaker verification (ASV) has recently achieved great progress. However, the performance of ASV degrades significantly when the test...
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Music Source Separation with Deep Convolution Neural Network
Audio source separation is the way in which we separate the sound origin from the audio site. Music origin partition is very essential for various...
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A Single-Channel EEG Automatic Artifact Rejection Framework Based on Hybrid Approach
Dealing with the physiological artifacts is a challenge in the period of recording electroencephalography (EEG), especially with a restricted number...
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Stripe-Transformer: deep stripe feature learning for music source separation
Music source separation (MSS) is to isolate musical instrument signals from the given music mixture. Stripes widely exist in music spectrograms,...
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Single Channel Blind Source Separation Under Deep Recurrent Neural Network
In wireless sensor networks, the signals received by sensors are usually complex nonlinear single-channel mixed signals. In practical applications,...
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SepMLP: An All-MLP Architecture for Music Source Separation
Most previous deep learning based methods use convolutional neural networks (CNNs) or Recurrent neural networks (RNNs) to model the separation...
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U-NET: A Supervised Approach for Monaural Source Separation
Separating speech is a challenging area of research, especially when trying to separate the desired source from its combination. Deep learning has...
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Single-Channel Speech Quality Enhancement in Mobile Networks Based on Generative Adversarial Networks
A large amount of randomly generated noise in mobile networks leads to a lack of targeting and gaming processes in the speech enhancement process,...
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Unsupervised speech separation by detecting speaker changeover points under single channel condition
In this paper, we propose a method to separate two speakers from a single channel speech mixture in an unsupervised way by detecting the speaker...
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Cycle GAN-Based Audio Source Separation Using Time–Frequency Masking
Audio source separation is addressed using time–frequency filtering and conditional adversarial networks. First, pitch tracks in the mixed audio are...
