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<blockquote data-quote="sihina_lahiru" data-source="post: 5845548" data-attributes="member: 149577"><p><img src="http://joinmovie.org/wp-content/uploads/2009/11/00109253_medium.jpeg" alt="" class="fr-fic fr-dii fr-draggable " style="" /></p><p></p><p>Speech Enhancement (Signals and Communication Technology)</p><p>Speech Enhancement (Signals and Communication Technology) | Jacob Benesty, Shoji Makino, Jingdong Chen | English</p><p>406 pages | Publisher: Springer; 1 edition (April 29, 2005) | ISBN-13: 978-3540240396 | 5.66 MB</p><p>We live in a noisy world! In all applications (telecommunications, hands-free communications, recording, human-machine interfaces, etc.) that require at least one microphone, the signal of interest is usually contaminated by noise and reverberation. As a result, the microphone signal has to be “cleaned” with digital signal processing tools before it is played out, transmitted, or stored. This book is about speech enhancement. Different well-known and state-of-the-art methods for noise reduction, with one or multiple microphones, are discussed. By speech enhancement, we mean not only noise reduction but also dereverberation and separation of independent signals.</p><p></p><p>These topics are also covered in this book. However, the general emphasis is on noise reduction because of the large number of applications that can benefit from this technology. The goal of this book is to provide a strong reference for researchers, engineers, and graduate students who are interested in the problem of signal and speech enhancement. To do so, we invited well-known experts to contribute chapters covering the state of the art in this focused field.</p><p></p><p>Amozon's Key Phrases - Statistically Improbable Phrases (SIPs):</p><p>signal model errors, source separat ion, frequency domain blind source separation, residual noise energy, speech leakage, voiced durations, speech dereverberation, based blind source separation, enhanced speech signal, hatch algorithm, ideal binary mask, microphone mismatch, signal subspace approach, varechoic chamber, reverberant signals, adaptive microphone array, step size matrix, spectral amplitude estimation, acoustic mixture, clean speech signal, speech coefficients, speech distortion, noise reduction performance, desired speech signal, noise redaction.</p><p></p><p> Code: <a href="http://hotfile.com/dl/17132066/8477b88/spchenh.rar.html" target="_blank">http://hotfile.com/dl/17132066/8477b88/spchenh.rar.html</a></p></blockquote><p></p>
[QUOTE="sihina_lahiru, post: 5845548, member: 149577"] [IMG]http://joinmovie.org/wp-content/uploads/2009/11/00109253_medium.jpeg[/IMG] Speech Enhancement (Signals and Communication Technology) Speech Enhancement (Signals and Communication Technology) | Jacob Benesty, Shoji Makino, Jingdong Chen | English 406 pages | Publisher: Springer; 1 edition (April 29, 2005) | ISBN-13: 978-3540240396 | 5.66 MB We live in a noisy world! In all applications (telecommunications, hands-free communications, recording, human-machine interfaces, etc.) that require at least one microphone, the signal of interest is usually contaminated by noise and reverberation. As a result, the microphone signal has to be “cleaned” with digital signal processing tools before it is played out, transmitted, or stored. This book is about speech enhancement. Different well-known and state-of-the-art methods for noise reduction, with one or multiple microphones, are discussed. By speech enhancement, we mean not only noise reduction but also dereverberation and separation of independent signals. These topics are also covered in this book. However, the general emphasis is on noise reduction because of the large number of applications that can benefit from this technology. The goal of this book is to provide a strong reference for researchers, engineers, and graduate students who are interested in the problem of signal and speech enhancement. To do so, we invited well-known experts to contribute chapters covering the state of the art in this focused field. Amozon's Key Phrases - Statistically Improbable Phrases (SIPs): signal model errors, source separat ion, frequency domain blind source separation, residual noise energy, speech leakage, voiced durations, speech dereverberation, based blind source separation, enhanced speech signal, hatch algorithm, ideal binary mask, microphone mismatch, signal subspace approach, varechoic chamber, reverberant signals, adaptive microphone array, step size matrix, spectral amplitude estimation, acoustic mixture, clean speech signal, speech coefficients, speech distortion, noise reduction performance, desired speech signal, noise redaction. Code: [url]http://hotfile.com/dl/17132066/8477b88/spchenh.rar.html[/url] [/QUOTE]
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