DeepAI AI Chat
Log In Sign Up

Multichannel Audio Source Separation with Independent Deeply Learned Matrix Analysis Using Product of Source Models

09/02/2021
by   Takuya Hasumi, et al.
0

Independent deeply learned matrix analysis (IDLMA) is one of the state-of-the-art multichannel audio source separation methods using the source power estimation based on deep neural networks (DNNs). The DNN-based power estimation works well for sounds having timbres similar to the DNN training data. However, the sounds to which IDLMA is applied do not always have such timbres, and the timbral mismatch causes the performance degradation of IDLMA. To tackle this problem, we focus on a blind source separation counterpart of IDLMA, independent low-rank matrix analysis. It uses nonnegative matrix factorization (NMF) as the source model, which can capture source spectral components that only appear in the target mixture, using the low-rank structure of the source spectrogram as a clue. We thus extend the DNN-based source model to encompass the NMF-based source model on the basis of the product-of-expert concept, which we call the product of source models (PoSM). For the proposed PoSM-based IDLMA, we derive a computationally efficient parameter estimation algorithm based on an optimization principle called the majorization-minimization algorithm. Experimental evaluations show the effectiveness of the proposed method.

READ FULL TEXT
01/16/2021

Minimum-volume Multichannel Nonnegative matrix factorization for blind source separation

Multichannel blind source separation aims to recover the latent sources ...
11/12/2013

Deep neural networks for single channel source separation

In this paper, a novel approach for single channel source separation (SC...
06/07/2021

Empirical Bayesian Independent Deeply Learned Matrix Analysis For Multichannel Audio Source Separation

Independent deeply learned matrix analysis (IDLMA) is one of the state-o...
03/08/2019

Fast Multichannel Source Separation Based on Jointly Diagonalizable Spatial Covariance Matrices

This paper describes a versatile method that accelerates multichannel so...
07/01/2020

Consistent Independent Low-Rank Matrix Analysis for Determined Blind Source Separation

Independent low-rank matrix analysis (ILRMA) is the state-of-the-art alg...
10/04/2017

Independent Low-Rank Matrix Analysis Based on Parametric Majorization-Equalization Algorithm

In this paper, we propose a new optimization method for independent low-...
07/04/2022

Semi-blind source separation using convolutive transfer function for nonlinear acoustic echo cancellation

The recently proposed semi-blind source separation (SBSS) method for non...