Sound field decomposition in reverberant environment using sparse and low-rank signal models

Shoichi Koyama; Hiroshi Saruwatari

ICASSP 2016accepted0 citations

Sound field decomposition in reverberant environment using sparse and low-rank signal models

Abstract

A sound field decomposition method for a reverberant environment is proposed. Sound field decomposition is the foundation of various acoustic signal processing applications and enables the estimation of the entire sound field from pressure measurements. Although spatial Fourier analysis of the sound field has been widely used, sparse decomposition of the sound field has recently been proved to be effective in several applications. However, in current methods, no constraints are imposed on ambiance components, whereas source components are assumed to be sparsely distributed in the space. This results in inaccurate decomposition in a reverberant environment. The proposed method is based on sparse and low-rank signal models, which are used for simultaneous decomposition of the observed signals into source and ambiance components. Numerical simulation results indicated that the decomposition accuracy is superior to that of current methods.

BibTeX

@inproceedings{icassp2016_soundfielddecomp,
  title = {Sound field decomposition in reverberant environment using sparse and low-rank signal models},
  author = {Shoichi Koyama and Hiroshi Saruwatari},
  booktitle = {ICASSP 2016},
  year = {2016}
}