BLIND SOURCE SEPARATION USING FREQUENCY INDEPENDENT COMPONENT ANALYSIS - Couverture souple

Okwelume, Gozie; K. Ezeude, Anayo

 
9783838338477: BLIND SOURCE SEPARATION USING FREQUENCY INDEPENDENT COMPONENT ANALYSIS
Couverture souple
ISBN 10 : 3838338472 ISBN 13 : 9783838338477
Editeur : LAP LAMBERT Academic Publishing, 2010

Synopsis

The need for speech enhancement is very important, because of the acoustic environment we are living in, which is composed of noise and other atmospheric disturbances, and this makes it almost impossible to record a speech signal in pure form. In most of the mixed signals there is usually no information about each source. In such situation the estimates of the original source signals is done based on the information of the received mixed signals, therefore the approach to be adopted in such cases to separate the signals must be one that does it blindly, thus the method Blind Source Separation is used in this work. Our thesis work focuses on Frequency domain Blind Source Separation (BSS) in which the received mixed signals are converted into the frequency domain and Independent Component Analysis (ICA) is applied at each frequency bin. Our main target in this project is to solve the permutation and scaling ambiguities in real time applications using the method proposed by Minje et al in [12]. Our results show that this method works better in an "offline" mixtures than in real time and lastly we gave some suggestions to improve the results.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

The need for speech enhancement is very important, because of the acoustic environment we are living in, which is composed of noise and other atmospheric disturbances, and this makes it almost impossible to record a speech signal in pure form. In most of the mixed signals there is usually no information about each source. In such situation the estimates of the original source signals is done based on the information of the received mixed signals, therefore the approach to be adopted in such cases to separate the signals must be one that does it blindly, thus the method Blind Source Separation is used in this work. Our thesis work focuses on Frequency domain Blind Source Separation (BSS) in which the received mixed signals are converted into the frequency domain and Independent Component Analysis (ICA) is applied at each frequency bin. Our main target in this project is to solve the permutation and scaling ambiguities in real time applications using the method proposed by Minje et al in [12]. Our results show that this method works better in an "offline" mixtures than in real time and lastly we gave some suggestions to improve the results.

Biographie de l'auteur

Gozie Okwelume, received his MSc degree in Elec. Eng. from Blekinge Inst. of Tech. Sweden in 2007. He worked as a Systems Manager at Hornitex Nigeria LTD. Kingsley Ezeude, received his MSc degree in Elec. Eng. from Blekinge Inst. of Tech. Sweden in 2007, and MSc in Information System from Concordia Uni. College of Alberta, Canada in 2010.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2010
Langue
anglais
ISBN 10 
3838338472
ISBN 13 
9783838338477
Reliure
Broché
Nombre de pages
64
Coordonnées du fabricant
non disponible
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