Hierarchical Neural Network Structures for Phoneme Recognition

The subject of this study is the role of hierarchical structures, based on neural networks, in identifying phonemes in automated speech recognition systems. It shows how the artificial neural network paradigm can simplify the analysis of spoken language. Read More

The subject of this study is the role of hierarchical structures, based on neural networks, in identifying phonemes in automated speech recognition systems. It shows how the artificial neural network paradigm can simplify the analysis of spoken language. Read Less

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  	This is a digital edition of this title. Rent eBook (5 Options) 30 Day Rental: $29.70 (Expires Aug 07, 2024) 60 Day Rental: $39.60 (Expires Sep 06, 2024) 90 Day Rental: $49.50 (Expires Oct 06, 2024) 120 Day Rental: $59.40 (Expires Nov 05, 2024) 180 Day Rental: $64.35 (Expires Jan 04, 2025) Buy eBook Lifetime Access: $99.00 Title: Hierarchical Neural Network Structures for Phoneme Recognition by Daniel Vasquez; Rainer Gruhn; Wolfgang Minker Publisher: Springer Nature Print ISBN: 9783642432101, 3642432107 eText ISBN: 9783642344251 Edition: 2014 2013 edition Format: PDF eBook	$29.70 Rent eBook This is a digital eBook Nothing will be shipped to you Works with web browsers and the VitalSource app on all Windows, Mac, Chromebook, Kindle Fire, iOS, and Android devices Most eBooks are returnable within 14 days of purchase Questions? See our eBook FAQ