9780128023983 - robust automatic speech recognition: a bridge to practical applications von li, jinyu; deng, li; haeb-umbach, reinhold; gong, yifan (5 Ergebnisse)
- Hardcover
- Erstausgabe
Anbieter: Better World Books, Mishawaka, IN, USABetter World Books
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EUR 105,26
Versand gratisVersand innerhalb von USAAnzahl: 1 verfügbar
Zustand: Good. 1st Edition. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.
- Hardcover
Anbieter: Majestic Books, Hounslow, Vereinigtes KönigreichMajestic Books
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EUR 105,12
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Zustand: New. pp. 250.
- Hardcover
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes KönigreichRia Christie Collections
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EUR 144,21
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Zustand: New. In.
- Hardcover
Anbieter: moluna, Greven, Deutschlandmoluna
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EUR 157,33
EUR 48,99 VersandVersand von Deutschland nach USAAnzahl: Mehr als 20 verfügbar
Zustand: New. The first book that provides a comprehensive review on noise and reverberation robust speech recognition methods in the era of deep neural networks Connects robust speech recognition techniques to machine learning paradigms with rigorous m.
- Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 216,00
EUR 63,73 VersandVersand von Deutschland nach USAAnzahl: 2 verfügbar
Buch. Zustand: Neu. Neuware - Robust Automatic Speech Recognition: A Bridge to Practical Applications establishes a solid foundation for automatic speech recognition that is robust against acoustic environmental distortion. It provides a thorough overview of classical and modern noise-and reverberation robust techniques that hav…e been developed over the past thirty years, with an emphasis on practical methods that have been proven to be successful and which are likely to be further developed for future applications.The strengths and weaknesses of robustness-enhancing speech recognition techniques are carefully analyzed. The book covers noise-robust techniques designed for acoustic models which are based on both Gaussian mixture models and deep neural networks. In addition, a guide to selecting the best methods for practical applications is provided.The reader will: Gain a unified, deep and systematic understanding of the state-of-the-art technologies for robust speech recognition Learn the links and relationship between alternative technologies for robust speech recognition Be able to use the technology analysis and categorization detailed in the book to guide future technology development Be able to develop new noise-robust methods in the current era of deep learning for acoustic modeling in speech recognition.
