| Titre : |
Blind speech separation : adaptive algorithm and implementation using UMA-16 v2 mic array testbed |
| Type de document : |
document électronique |
| Auteurs : |
Merah, Idriss, Auteur ; Ghecham, Ahmed-Zakaria, Auteur ; Adel Belouchrani, Directeur de thèse ; Soufiane Tebache, Directeur de thèse |
| Editeur : |
[S.l.] : [s.n.] |
| Année de publication : |
2023 |
| Importance : |
1 fichier PDF (15 Mo) |
| Présentation : |
ill. |
| Note générale : |
Mode d'accès : accès au texte intégral par intranet.
Mémoire de Projet de Fin d’Etudes : Electronique : Alger, Ecole Nationale Polytechnique : 2023
Bibliogr. p. 104 - 108 |
| Langues : |
Anglais (eng) |
| Mots-clés : |
Blind source separation
IVA
Whitening |
| Index. décimale : |
PN00523 |
| Résumé : |
In an environment where multiple recorded individuals are speaking simultaneously, it is difficult to discern each voice. Therefore, extracting each speech signal from this convoluted mixture is crucial and has several applications. The objective of this work is to perform blind source separation in an adaptive manner. First, we studied the Independent Vector Analysis (IVA) algorithm to fully understand its principle. Then, we modified the algorithm to obtain its adaptive version and added adaptive data whitening to it. Finally, we compared the effects of this whitening on the performance of our algorithm and implemented this method using real signals recorded through an array of microphones |
Blind speech separation : adaptive algorithm and implementation using UMA-16 v2 mic array testbed [document électronique] / Merah, Idriss, Auteur ; Ghecham, Ahmed-Zakaria, Auteur ; Adel Belouchrani, Directeur de thèse ; Soufiane Tebache, Directeur de thèse . - [S.l.] : [s.n.], 2023 . - 1 fichier PDF (15 Mo) : ill. Mode d'accès : accès au texte intégral par intranet.
Mémoire de Projet de Fin d’Etudes : Electronique : Alger, Ecole Nationale Polytechnique : 2023
Bibliogr. p. 104 - 108 Langues : Anglais ( eng)
| Mots-clés : |
Blind source separation
IVA
Whitening |
| Index. décimale : |
PN00523 |
| Résumé : |
In an environment where multiple recorded individuals are speaking simultaneously, it is difficult to discern each voice. Therefore, extracting each speech signal from this convoluted mixture is crucial and has several applications. The objective of this work is to perform blind source separation in an adaptive manner. First, we studied the Independent Vector Analysis (IVA) algorithm to fully understand its principle. Then, we modified the algorithm to obtain its adaptive version and added adaptive data whitening to it. Finally, we compared the effects of this whitening on the performance of our algorithm and implemented this method using real signals recorded through an array of microphones |
|
PN00100 
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