Blind Speech Separation (eBook, PDF)

Redaktion: Makino, Shoji; Sawada, Hiroshi; Lee, Te-Won

• Format: PDF

Produktbeschreibung

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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Produktdetails

• Verlag: Springer Netherlands
• Seitenzahl: 432
• Erscheinungstermin: 7. September 2007
• Englisch
• ISBN-13: 9781402064791
• Artikelnr.: 37361645

Autorenporträt

Dr. Shoji Makino is an IEEE Fellow, Associate Editor of the IEEE Transactions on Speech & Audio Processing, and Executive Manager NTT Communication Science Laboratories. Dr. Makino was also co-editor on the succesful 2005 Springer book: Benesty - Speech Enhancement.

Inhaltsangabe

Multiple Microphone Blind Speech Separation with ICA.- Convolutive Blind Source Separation for Audio Signals.- Frequency-Domain Blind Source Separation.- Blind Source Separation using Space-Time Independent Component Analysis.- TRINICON-based Blind System Identification with Application to Multiple-Source Localization and Separation.- SIMO-Model-Based Blind Source Separation - Principle and its Applications.- Independent Vector Analysis for Convolutive Blind Speech Separation.- Relative Newton and Smoothing Multiplier Optimization Methods for Blind Source Separation.- Underdetermined Blind Speech Separation with Sparseness.- The DUET Blind Source Separation Algorithm.- K-means Based Underdetermined Blind Speech Separation.- Underdetermined Blind Source Separation of Convolutive Mixtures by Hierarchical Clustering and L1-Norm Minimization.- Bayesian Audio Source Separation.- Single Microphone Blind Speech Separation.- Monaural Source Separation.- Probabilistic Decompositions of Spectra for Sound Separation.- Sparsification for Monaural Source Separation.- Monaural Speech Separation by Support Vector Machines: Bridging the Divide Between Supervised and Unsupervised Learning Methods.