| Titre : |
Blind speech separation |
| Type de document : |
document électronique |
| Auteurs : |
Shiba, Shoji, Auteur ; Lee, Te-Won, Auteur |
| Editeur : |
Berlin ; London ; Cham : Springer |
| Année de publication : |
2007 |
| Collection : |
Signals and communication technology |
| ISBN/ISSN/EAN : |
978-1-4020-6479-1 |
| Langues : |
Anglais (eng) |
| Mots-clés : |
Télécommunication Engineering Signal, Image and Speech Processing |
| Résumé : |
This is the first book to provide a cutting edge reference to the fascinating topic of blind source separation (BSS) for convolved speech mixtures. Through contributions by the foremost experts on the subject, the book provides an up-to-date account of research findings, explains the underlying theory, and discusses potential applications. The individual chapters are designed to be tutorial in nature with specific emphasis on an in-depth treatment of state of the art techniques.
Blind Speech Separation is divided into three parts:
Part 1 presents overdetermined or critically determined BSS. Here the main technology is independent component analysis (ICA). ICA is a statistical method for extracting mutually independent sources from their mixtures. This approach utilizes spatial diversity to discriminate between desired and undesired components, i.e., it reduces the undesired components by forming a spatial null towards them. It is, in fact, a blind adaptive beamformer realized by unsupervised adaptive filtering.
Part 2 addresses underdetermined BSS, where there are fewer microphones than source signals. Here, the sparseness of speech sources is very useful; we can utilize time-frequency diversity, where sources are active in different regions of the time-frequency plane.
Part 3 presents monaural BSS where there is only one microphone. Here, we can separate a mixture by using the harmonicity and temporal structure of the sources. We can build a probabilistic framework by assuming a source model, and separate a mixture by maximizing the a posteriori probability of the sources. |
Blind speech separation [document électronique] / Shiba, Shoji, Auteur ; Lee, Te-Won, Auteur . - Berlin ; London ; Cham : Springer, 2007. - ( Signals and communication technology) . ISBN : 978-1-4020-6479-1 Langues : Anglais ( eng)
| Mots-clés : |
Télécommunication Engineering Signal, Image and Speech Processing |
| Résumé : |
This is the first book to provide a cutting edge reference to the fascinating topic of blind source separation (BSS) for convolved speech mixtures. Through contributions by the foremost experts on the subject, the book provides an up-to-date account of research findings, explains the underlying theory, and discusses potential applications. The individual chapters are designed to be tutorial in nature with specific emphasis on an in-depth treatment of state of the art techniques.
Blind Speech Separation is divided into three parts:
Part 1 presents overdetermined or critically determined BSS. Here the main technology is independent component analysis (ICA). ICA is a statistical method for extracting mutually independent sources from their mixtures. This approach utilizes spatial diversity to discriminate between desired and undesired components, i.e., it reduces the undesired components by forming a spatial null towards them. It is, in fact, a blind adaptive beamformer realized by unsupervised adaptive filtering.
Part 2 addresses underdetermined BSS, where there are fewer microphones than source signals. Here, the sparseness of speech sources is very useful; we can utilize time-frequency diversity, where sources are active in different regions of the time-frequency plane.
Part 3 presents monaural BSS where there is only one microphone. Here, we can separate a mixture by using the harmonicity and temporal structure of the sources. We can build a probabilistic framework by assuming a source model, and separate a mixture by maximizing the a posteriori probability of the sources. |
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