Independent component analysis for separation of speech mixtures : a comparison among thirty algorithms
Author
Source
The Iraqi Journal of Electrical and Electronic Engineering
Issue
Vol. 11, Issue 1 (30 Jun. 2015), pp.1-9, 9 p.
Publisher
University of Basrah College of Engineering
Publication Date
2015-06-30
Country of Publication
Iraq
No. of Pages
9
Main Subjects
Information Technology and Computer Science
Abstract EN
Vast number of researches deliberated the separation of speech mixtures due to the importance of this field of research.
Whereas its applications became widely used in our daily life; such as mobile conversation, video conferences, and other distant communications.
These sorts of applications may suffer from what is well known the cocktail party problem.
Independent component analysis (ICA) has been extensively used to overcome this problem and many ICA algorithms based on different techniques have been developed in this context.
Still coming up with some suitable algorithms to separate speech mixed signals into their original ones is of great importance.
Hence, this paper utilizes thirty ICA algorithms for estimating the original speech signals from mixed ones, the estimation process is carried out with the purpose of testing the robustness of the algorithms once against a different number of mixed signals and another against different lengths of mixed signals.
Three criteria namely Spearman correlation coefficient, signal to interference ratio, and computational demand have been used for comparing the obtained results.
The results of the comparison were sufficient to signify some algorithms which are appropriate for the separation of speech mixtures.
American Psychological Association (APA)
al-Sayigh, Ali. 2015. Independent component analysis for separation of speech mixtures : a comparison among thirty algorithms. The Iraqi Journal of Electrical and Electronic Engineering،Vol. 11, no. 1, pp.1-9.
https://search.emarefa.net/detail/BIM-583644
Modern Language Association (MLA)
al-Sayigh, Ali. Independent component analysis for separation of speech mixtures : a comparison among thirty algorithms. The Iraqi Journal of Electrical and Electronic Engineering Vol. 11, no. 1 (2015), pp.1-9.
https://search.emarefa.net/detail/BIM-583644
American Medical Association (AMA)
al-Sayigh, Ali. Independent component analysis for separation of speech mixtures : a comparison among thirty algorithms. The Iraqi Journal of Electrical and Electronic Engineering. 2015. Vol. 11, no. 1, pp.1-9.
https://search.emarefa.net/detail/BIM-583644
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 8-9
Record ID
BIM-583644