How can we engineer systems capable of "cocktail party" listening?
Human listeners are able to perceptually segregate one sound source from an acoustic mixture, such as a single voice from a mixture of other voices and music at a busy cocktail party. How can we engineer "machine listening" systems that achieve this perceptual feat?
Albert Bregman's book Auditory Scene Analysis, published in 1990, drew an analogy between the perception of auditory scenes and visual scenes, and described a coherent framework for understanding the perceptual organization of sound. His account has stimulated much interest in computational studies of hearing. Such studies are motivated in part by the demand for practical sound separation systems, which have many applications including noise-robust automatic speech recognition, hearing prostheses, and automatic music transcription. This emerging field has become known as computational auditory scene analysis (CASA).
Computational Auditory Scene Analysis: Principles, Algorithms, and Applications provides a comprehensive and coherent account of the state of the art in CASA, in terms of the underlying principles, the algorithms and system architectures that are employed, and the potential applications of this exciting new technology. With a Foreword by Bregman, its chapters are written by leading researchers and cover a wide range of topics including:
The text is written at a level that will be accessible to graduate students and researchers from related science and engineering disciplines. The extensive bibliography accompanying each chapter will also make this book a valuable reference source. A web site accompanying the text, http: //www.casabook.org, features software tools and sound demonstrations.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Editors DeLIANG WANG and GUY J. BROWN are well-known for their contributions to the development of CASA. Wang is a Professor in the Department of Computer Science and Engineering and the Center for Cognitive Science at The Ohio State University. He is an IEEE Fellow. Brown is a Senior Lecturer in the Department of Computer Science at the University of Sheffield, UK.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Hardcover. Etat : new. Hardcover. How can we engineer systems capable of "cocktail party" listening? Human listeners are able to perceptually segregate one sound source from an acoustic mixture, such as a single voice from a mixture of other voices and music at a busy cocktail party. How can we engineer "machine listening" systems that achieve this perceptual feat? Albert Bregman's book Auditory Scene Analysis, published in 1990, drew an analogy between the perception of auditory scenes and visual scenes, and described a coherent framework for understanding the perceptual organization of sound. His account has stimulated much interest in computational studies of hearing. Such studies are motivated in part by the demand for practical sound separation systems, which have many applications including noise-robust automatic speech recognition, hearing prostheses, and automatic music transcription. This emerging field has become known as computational auditory scene analysis (CASA). Computational Auditory Scene Analysis: Principles, Algorithms, and Applications provides a comprehensive and coherent account of the state of the art in CASA, in terms of the underlying principles, the algorithms and system architectures that are employed, and the potential applications of this exciting new technology. With a Foreword by Bregman, its chapters are written by leading researchers and cover a wide range of topics including: Estimation of multiple fundamental frequenciesFeature-based and model-based approaches to CASASound separation based on spatial locationProcessing for reverberant environmentsSegregation of speech and musical signalsAutomatic speech recognition in noisy environmentsNeural and perceptual modeling of auditory organization The text is written at a level that will be accessible to graduate students and researchers from related science and engineering disciplines. The extensive bibliography accompanying each chapter will also make this book a valuable reference source. A web site accompanying the text, , features software tools and sound demonstrations. How can we engineer systems capable of "cocktail party" listening? Human listeners are able to perceptually segregate one sound source from an acoustic mixture, such as a single voice from a mixture of other voices and music at a busy cocktail party. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9780471741091
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Etat : New. How can we engineer systems capable of "cocktail party" listening? Human listeners are able to perceptually segregate one sound source from an acoustic mixture, such as a single voice from a mixture of other voices and music at a busy cocktail party. Editor(s): Wang, DeLiang; Brown, Guy J. Num Pages: 396 pages, Illustrations. BIC Classification: UYU. Category: (P) Professional & Vocational. Dimension: 235 x 165 x 25. Weight in Grams: 720. . 2006. 1st Edition. Hardcover. . . . . N° de réf. du vendeur V9780471741091
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