There are 11 repositories under blind-source-separation topic.
A fast implementation of bss_eval metrics for blind source separation
A UNIFIED SPEECH ENHANCEMENT FRONT-END FOR ONLINE DEREVERBERATION, ACOUSTIC ECHO CANCELLATION, AND SOURCE SEPARATION
A repository of awesome Non-Intrusive Load Monitoring(NILM) with code.
Multi-NILM: Multi Label Non Intrusive Load Monitoring
X. Wang, Y. Zhong, L. Zhang, and Y. Xu, “Spatial Group Sparsity Regularized Nonnegative Matrix Factorization for Hyperspectral Unmixing,” IEEE Transactions on Geoscience and Remote Sensing, vol. 55, no. 11, pp.6287-6304, 2017.
A New Perspective of Auxiliary-Function-Based Independent Component Analysis in Acoustic Echo Cancellation
Code to do blind source separation with more microphones than sources using auxilliary based independent vector analysis.
REPeating Pattern Extraction Technique (REPET) in Matlab for audio source separation: original REPET, REPET extended, adaptive REPET, REPET-SIM, REPET-SIM online
REPeating Pattern Extraction Technique (REPET) in Python for audio source separation: original REPET, REPET extended, adaptive REPET, REPET-SIM, online REPET-SIM
Repository for the IEEE/ACM TASLP 2023 Paper "Zero-Note Samba: Self-Supervised Beat Tracking".
Generalized Minimal Distortion Principle for Blind Source Separation
A python based Machine Learning project that separates two sounds intermixed.
Implementation of surface EMG decomposition as proposed on Francesco Negro et al 2016 J. Neural Eng. 13 026027.
A blind source separation package using non-negative matrix factorization and non-negative ICA
Multimodal formulation of IVA using conventional microphones and power sensing blinkies.
A model for Blind Source Separation using Dictionary Learning
A convolutional neural network for blind audio source separation.
A Python library for blind source separation.
Official repository for "Blind Source Separation of Single-Channel Mixtures via Multi-Encoder Autoencoders".
Nonnegative Matrix Factorization + k-means clustering and physics constraints for Unsupervised and Physics-Informed Machine Learning
Smart Tensors Tutorials
Directional sparse filtering for blind speech separation
Python Implementation for Directional Sparse Filtering with Tensorflow/Keras
Python versions of Independent Vector Analysis (IVA-G and IVA-L-SOS).
Fast implementations of FastICA and DUET for blind source separation
Tensor Extraction of Latent Features (T-ELF). Within T-ELF's arsenal are non-negative matrix and tensor factorization solutions, equipped with automatic model determination (also known as the estimation of latent factors - rank) for accurate data modeling. Our software suite encompasses cutting-edge data pre-processing and post-processing modules.
An exploration of blind source audio separation using spiking neural networks. Latency, power. and intelligibility are primary objectives while bio-plausibility is left as a secondary objective to be addressed in the future.