Detail publikace

Optimizing dictionary learning parameters for solving Audio Inpainting problem

MACH, V. OZDOBINSKI, R.

Originální název

Optimizing dictionary learning parameters for solving Audio Inpainting problem

Typ

článek v časopise - ostatní, Jost

Jazyk

angličtina

Originální abstrakt

Recovering missing or distorted audio signal samples has been recently improved by solving an Audio Inpainting problem. This paper aims to connect this problem with K-SVD dictionary learning to improve reconstruction error for missing signal insertion problem. Our aim is to adapt an initial dictionary to the reliable signal to be more accurate in missing samples estimation. This approach is based on sparse signals reconstruction and optimization problem. In the paper two staple algorithms, connection between them and emerging problems are described. We tried to find optimal parameters for efficient dictionary learning.

Klíčová slova

Audio Inpainting, Dictionary Learning, K-SVD, Orthogonal Matching Pursuit, Signal reconstruction, Sparse Representations

Autoři

MACH, V.; OZDOBINSKI, R.

Rok RIV

2013

Vydáno

7. 1. 2013

Místo

Brno

ISSN

1805-5443

Periodikum

International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems

Ročník

2

Číslo

1

Stát

Česká republika

Strany od

40

Strany do

45

Strany počet

6

URL

http://www.ijates.org/index.php/ijates/article/view/34/32

BibTex

@article{BUT96562,
  author="Václav {Mach} and Roman {Ozdobinski}",
  title="Optimizing dictionary learning parameters for solving Audio Inpainting problem",
  journal="International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems",
  year="2013",
  volume="2",
  number="1",
  pages="40--45",
  issn="1805-5443",
  url="http://www.ijates.org/index.php/ijates/article/view/34/32"
}