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Audio source separation and speech enhancement /
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 be...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Hoboken, NJ :
John Wiley & Sons,
[2018]
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| Temas: | |
| Acceso en línea: | Texto completo Texto completo |
MARC
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| 245 | 0 | 0 | |a Audio source separation and speech enhancement / |c edited by Emmanuel Vincent, Tuomas Virtanen, Sharon Gannot. |
| 264 | 1 | |a Hoboken, NJ : |b John Wiley & Sons, |c [2018] | |
| 264 | 4 | |c ©2018 | |
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| 504 | |a Includes bibliographical references and index. | ||
| 588 | 0 | |a Description based on online resource; title from PDF title page (Wiley platform, viewed on October 25, 2023). | |
| 520 | |a 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. | ||
| 505 | 0 | |a Preface / Emmanuel Vincent, Tuomas Virtanen, Sharon Gannot -- | |
| 505 | 8 | |a 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 | |a 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 | |a 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 | |a 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. | |
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 590 | |a ProQuest Ebook Central |b Ebook Central Academic Complete | ||
| 650 | 0 | |a Speech processing systems. | |
| 650 | 0 | |a Automatic speech recognition. | |
| 650 | 6 | |a Traitement automatique de la parole. | |
| 650 | 6 | |a Reconnaissance automatique de la parole. | |
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| 650 | 7 | |a Automatic speech recognition |2 fast | |
| 650 | 7 | |a Speech processing systems |2 fast | |
| 700 | 1 | |a Vincent, Emmanuel |c (Research scientist), |e editor. | |
| 700 | 1 | |a Virtanen, Tuomas, |e editor. | |
| 700 | 1 | |a Gannot, Sharon, |e editor. | |
| 758 | |i has work: |a Audio source separation and speech enhancement (Text) |1 https://id.oclc.org/worldcat/entity/E39PCGvfRgXjTKQwtXgqfBVf7b |4 https://id.oclc.org/worldcat/ontology/hasWork | ||
| 776 | 0 | 8 | |i Print version: |t Audio source separation and speech enhancement. |d Hoboken, NJ : John Wiley & Sons, 2018 |z 9781119279891 |w (DLC) 2018013163 |
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