virtanen tuomas (19 Ergebnisse)

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New. In.

Zustand: New.

Hardcover. Zustand: Brand New. 1st edition. 514 pages. 9.75x6.75x1.00 inches. In Stock.

Zustand: New. With the growing use of automatic speech recognition (ASR) in everyday life, the ability to solve problems in recorded speech is critical for engineers and researchers developing ASR technologies. The only resource of its kind, this book presents a comprehensive survey of state-of-the-art techniques used to improve the robustness of ASR systems. Editor(s): Virtanen, Tuomas; Singh, Rita; Raj, Bhiksha. Num Pages: 514 pages, Illustrations. BIC Classification: UYQS. Category: (P) Professional & Vocational. Dimension: 247 x 175 x 29. Weight in Grams: 918. . 2012. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.

Hardcover. Zustand: Brand New. 470 pages. 9.75x6.75x1.25 inches. In Stock.

Zustand: New. EMMANUEL VINCENT is a Senior Research Scientist with Inria, Nancy, France. His research focuses on machine learning for speech and audio signal processing. He has been working on audio source separation for 15 years and co-authored over 180 publications in .

Zustand: New. 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. Num Pages: 512 pages. BIC Classification: TJ. Category: (P) Professional & Vocational. Dimension: 244 x 170. . . 2018. Hardcover. . . . . Books ship from the US and Ireland.

Hardcover. Zustand: Brand New. 470 pages. 9.75x6.75x1.25 inches. In Stock.

Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 514 | Sprache: Englisch | Produktart: Bücher | Automatic speech recognition (ASR) systems are finding increasing use in everyday life. Many of the commonplace environments where the systems are used are noisy, for example users calling up a voice search system from a busy cafeteria or a street. This can result in degraded speech recordings and adversely affect the performance of speech recognition systems.  As the use of ASR systems increases, knowledge of the state-of-the-art in techniques to deal with such problems becomes critical to system and application engineers and researchers who work with or on ASR technologies. This book presents a comprehensive survey of the state-of-the-art in techniques used to improve the robustness of speech recognition systems to these degrading external influences. Key features: Reviews all the main noise robust ASR approaches, including signal separation, voice activity detection, robust feature extraction, model compensation and adaptation, missing data techniques and recognition of reverberant speech. Acts as a timely exposition of the topic in light of more widespread use in the future of ASR technology in challenging environments. Addresses robustness issues and signal degradation which are both key requirements for practitioners of ASR. Includes contributions from top ASR researchers from leading research units in the field.

Zustand: New.

Zustand: New.

Buch. Zustand: Neu. Neuware - Learn the technology behind hearing aids, Siri, and EchoAudio 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.

Taschenbuch. Zustand: Neu. Computational Analysis of Sound Scenes and Events | Tuomas Virtanen (u. a.) | Taschenbuch | x | Englisch | 2018 | Springer | EAN 9783319875590 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents computational methods for extracting the useful information from audio signals, collecting the state of the art in the field of sound event and scene analysis. The authors cover the entire procedure for developing such methods, ranging from data acquisition and labeling, through the design of taxonomies used in the systems, to signal processing methods for feature extraction and machine learning methods for sound recognition. The book also covers advanced techniques for dealing with environmental variation and multiple overlapping sound sources, and taking advantage of multiple microphones or other modalities. The book gives examples of usage scenarios in large media databases, acoustic monitoring, bioacoustics, and context-aware devices. Graphical illustrations of sound signals and their spectrographic representations are presented, as well as block diagrams and pseudocode of algorithms.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents computational methods for extracting the useful information from audio signals, collecting the state of the art in the field of sound event and scene analysis. The authors cover the entire procedure for developing such methods, ranging from data acquisition and labeling, through the design of taxonomies used in the systems, to signal processing methods for feature extraction and machine learning methods for sound recognition. The book also covers advanced techniques for dealing with environmental variation and multiple overlapping sound sources, and taking advantage of multiple microphones or other modalities. The book gives examples of usage scenarios in large media databases, acoustic monitoring, bioacoustics, and context-aware devices. Graphical illustrations of sound signals and their spectrographic representations are presented, as well as block diagrams and pseudocode of algorithms.

Paperback. Zustand: Brand New. reprint edition. 422 pages. 9.25x6.10x0.98 inches. In Stock.

Zustand: new. Pages: 392 Language: Finnish. 9789511350491.