Laplacian Mixture Modeling for Overcomplete Mixture Matrix Estimation in Wavelet Packet Domain by Adaptive EM-type Algorithm

Author

Tinati, M.A. ; Mozaffary, B.

Author_Institution

Fac. of Electr. Eng., Tabriz Univ.

fYear

2006

fDate

7-9 June 2006

Firstpage

1

Lastpage

5

Abstract

Speech process has benefited a great deal from the wavelet transforms. Wavelet packets decompose signals in to broader components using linear spectral bisecting. In this paper, mixtures of speech signals are decomposed using wavelet packets, the phase difference between the two mixtures are investigated in wavelet domain. In our method Laplacian mixture model (LMM) is defined. An expectation maximization (EM) algorithm is used for training of the model and calculation of model parameters which is the mixture matrix. Therefore individual speech components of speech mixtures are separated

Keywords

expectation-maximisation algorithm; speech processing; wavelet transforms; Laplacian mixture modeling; blind source separation; expectation maximization algorithm; mixture matrix estimation; speech mixtures; speech processing; speech signal; wavelet packet domain; Continuous wavelet transforms; Discrete wavelet transforms; Independent component analysis; Laplace equations; Matrix decomposition; Signal processing algorithms; Source separation; Speech; Wavelet domain; Wavelet packets; Blind Source Separation; Expectation Maximization; ICA; Laplacian Mixture Model; Speech Processing; wavelet packets;

fLanguage

English

Publisher

ieee

Conference_Titel

Cybernetics and Intelligent Systems, 2006 IEEE Conference on

Conference_Location

Bangkok

Print_ISBN

1-4244-0023-6

Type

conf

DOI

10.1109/ICCIS.2006.252352

Filename

4017911