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020 1119279895
020 9781119279891
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099 eBook O'Reilly for Public Libraries
245 00 Audio source separation and speech enhancement /|cedited
by Emmanuel Vincent, Tuomas Virtanen, Sharon Gannot.
|h[O'Reilly electronic resource]
264 1 Hoboken, NJ :|bJohn Wiley & Sons,|c[2018]
264 4 |c©2018
300 1 online resource
336 text|btxt|2rdacontent
337 computer|bc|2rdamedia
338 online resource|bcr|2rdacarrier
504 Includes bibliographical references and index.
505 0 Preface / Emmanuel Vincent, Tuomas Virtanen, Sharon Gannot
--
505 8 Part I: Prerequisites: Introduction / Emmanuel Vincent,
Sharon Gannot, and Tuomas Virtanen -- Time-frequency
processing : spectral properties / Tuomas Virtanen,
Emmanuel Vincent, and Sharon Gannot -- Acoustics : spatial
properties / Emmanuel Vincent, Sharon Gannot, and Tuomas
Virtanen -- Multichannel source activity detection,
localization, and tracking / Pasi Pertilä, Alessio Brutti,
Piergiogio Svaizer, and Maurizio Omologo --
505 8 Part II: Single-Channel Separation and Enhancement:
Spectral masking and filtering / Timo Gerkmann and
Emmanuel Vincent -- Single-channel speech presence
probability estimation and noise tracking / Rainer Martin
and Israel Cohen -- Single-channel classivication and
clustering approaches / Felix Weninger, Jun Du, Erik
Marchi, and Tian Gao -- Nonnegative matrix factorization /
Roland Badeau and Tuomas Virtanen -- Temporal extensions
of nonegative matrix factorization / Cédric Févotte, Paris
Smaragdis, Nasser Mohammadiha, and Gautham J. Mysore --
505 8 Part III: Multichannel Separation and Enhancement: Spatial
filtering / Shmulik Markovich-Golan, Walter Kellermann,
and Sharon Gannot -- Multichannel parameter estimation /
Shmulik Markovich-Golan, Walter Kellermann, and Sharon
Gannot -- Multichannel clustering and classification
approaches / Michael I. Mandel, Shoko Araki, and Tomohiro
Nakatani -- Independent component and vector analysis /
Hiroshi Sawada and Zbyněk Kokdovský -- Gaussian model
based multichannel separation / Alexey Ozerov and Hirokazu
Kameoka -- Dereverberation / Emanuël A.P. Habets and
Patrick A. Naylor --
505 8 Part IV: Application Scenarios and Perspectives: Applying
source separation to music / Bryan Pardo, Antoine Liutkus,
Zhiyao Duan, and Gaël Richard -- Application of source
separation to robust speech analysis and recognition /
Shinji Watanabe, Tuomas Virtanen, and Dorothea Kolossa --
Binaural speech processing with application to hearing
devices / Simon Doclo, Sharon Gannot, Daniel Marquardt,
and Elior Hadad -- Perspectives / Emmanual Vincent, Tuomas
Virtanen, and Sharon Gannot.
520 Learn the technology behind hearing aids, Siri, and Echo
Audio source separation and speech enhancement aim to
extract one or more source signals of interest from an
audio recording involving several sound sources. These
technologies are among the most studied in audio signal
processing today and bear a critical role in the success
of hearing aids, hands-free phones, voice command and
other noise-robust audio analysis systems, and music post-
production software. Research on this topic has followed
three convergent paths, starting with sensor array
processing, computational auditory scene analysis, and
machine learning based approaches such as independent
component analysis, respectively. This book is the first
one to provide a comprehensive overview by presenting the
common foundations and the differences between these
techniques in a unified setting. Key features: -
Consolidated perspective on audio source separation and
speech enhancement.-Both historical perspective and latest
advances in the field, e.g. deep neural networks.-Diverse
disciplines: array processing, machine learning, and
statistical signal processing.-Covers the most important
techniques for both single-channel and multichannel
processing. This book provides both introductory and
advanced material suitable for people with basic knowledge
of signal processing and machine learning. Thanks to its
comprehensiveness, it will help students select a
promising research track, researchers leverage the
acquired cross-domain knowledge to design improved
techniques, and engineers and developers choose the right
technology for their target application scenario. It will
also be useful for practitioners from other fields (e.g.,
acoustics, multimedia, phonetics, and musicology) willing
to exploit audio source separation or speech enhancement
as pre-processing tools for their own needs.
588 0 Description based on online resource; title from PDF title
page (Wiley platform, viewed on October 25, 2023).
590 O'Reilly|bO'Reilly Online Learning: Academic/Public
Library Edition
650 0 Speech processing systems.
650 0 Automatic speech recognition.
650 6 Traitement automatique de la parole.
650 6 Reconnaissance automatique de la parole.
650 7 Automatic speech recognition|2fast
650 7 Speech processing systems|2fast
700 1 Vincent, Emmanuel|c(Research scientist),|eeditor.
700 1 Virtanen, Tuomas,|eeditor.
700 1 Gannot, Sharon,|eeditor.
776 08 |iPrint version:|tAudio source separation and speech
enhancement.|dHoboken, NJ : John Wiley & Sons, 2018
|z9781119279891|w(DLC) 2018013163
856 40 |uhttps://ezproxy.naperville-lib.org/login?url=https://
learning.oreilly.com/library/view/~/9781119279891/?ar
|zAvailable on O'Reilly for Public Libraries
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