Low-Complexity Recursive-Least-Squares-Based Online Nonnegative Matrix Factorization Algorithm for Audio Source Separation

Seokjin LEE  

Publication
IEICE TRANSACTIONS on Information and Systems   Vol.E100-D   No.5   pp.1152-1156
Publication Date: 2017/05/01
Publicized: 2017/02/06
Online ISSN: 1745-1361
DOI: 10.1587/transinf.2016EDL8226
Type of Manuscript: LETTER
Category: Music Information Processing
Keyword: 
nonnegative matrix factorization (NMF),  online nonnegatie matrix factorization (ONMF),  recursive least squares (RLS),  low complexity,  audio source separation,  

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Summary: 
An online nonnegative matrix factorization (NMF) algorithm based on recursive least squares (RLS) is described in a matrix form, and a simplified algorithm for a low-complexity calculation is developed for frame-by-frame online audio source separation system. First, the online NMF algorithm based on the RLS method is described as solving the NMF problem recursively. Next, a simplified algorithm is developed to approximate the RLS-based online NMF algorithm with low complexity. The proposed algorithm is evaluated in terms of audio source separation, and the results show that the performance of the proposed algorithms are superior to that of the conventional online NMF algorithm with significantly reduced complexity.