Independent Deeply Learned Matrix Analysis for Determined Audio Source Separation

Development of Independent Component Analysis Based Blind Source Separation Algorithms for Audio /Image Separation

Supervised non-negative matrix factorization for audio source separation

Source separation is a widely studied problems in signal processing. Despite the permanent progress reported in the literature it is still considered a significant challenge. This chapter first reviews the use of non-negative matrix factorization (NMF) algorithms for solving source separation problems, and proposes a new way for the supervised training in NMF. Matrix factorization methods have ...

Bayesian audio source separation

In this chapter we describe a Bayesian approach to audio source separation. The approach relies on probabilistic modeling of sound sources as (sparse) linear combinations of atoms from a dictionary and Markov chain Monte Carlo (MCMC) inference. Several prior distributions are considered for the source expansion coefficients. We first consider independent and identically distributed (iid) genera...

Independent component analysis and blind source separation

Independent Component Analysis and Blind Source Separation