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Herausgeber: 
  • Sharon Gannot
  • Emmanuel Vincent
  • Tuomas Virtanen
  • Audio Source Separation and Speech Enhancement 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 2 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Oktober 2018  
    Genre:  Naturwissensch., Medizin, Technik 
     
    Audio & Speech Processing & Broadcasting / Audio-, Sprachverarbeitung u. Übertragung / Audiotechnik / Electrical & Electronics Engineering / Elektrotechnik u. Elektronik
    ISBN:  9781119279891 
    EAN-Code: 
    9781119279891 
    Verlag:  Wiley 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 244 mm / B 170 mm / D 15 mm 
    Gewicht:  666 gr 
    Seiten:  504 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    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.

      



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