Skip to main content
Article thumbnail
Location of Repository

BLIND SEPARATION OF INFINITELY MANY SPARSE SOURCES

By Hirokazu Kameoka, Misa Sato, Takuma Ono, Nobutaka Ono and Shigeki Sagayama

Abstract

This paper deals with the problem of underdetermined blind source separation (BSS) where the number of sources is unknown. We propose a BSS approach that simultaneously estimates the number of sources, separates the sources based on the sparseness of speech, and performs permutation alignment. We confirmed experimentally that reasonably good separation was obtained with the present method without specifying the number of sources. Index Terms — Underdetermined blind source separation, sparseness, Dirichlet process, variational inference 1

Year: 2013
OAI identifier: oai:CiteSeerX.psu:10.1.1.309.2671
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://citeseerx.ist.psu.edu/v... (external link)
  • http://www.brl.ntt.co.jp/peopl... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.