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Hierarchical Neural Network Structures for Phoneme Recognition (Paperback) Loot Price: R3,173
Discovery Miles 31 730
Repayment Terms: R297 pm x 12*
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Hierarchical Neural Network Structures for Phoneme Recognition (Paperback): Daniel Vasquez, Rainer Gruhn, Wolfgang Minker

Hierarchical Neural Network Structures for Phoneme Recognition (Paperback)

Daniel Vasquez, Rainer Gruhn, Wolfgang Minker

Series: Signals and Communication Technology

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Loot Price R3,173 Discovery Miles 31 730 | Repayment Terms: R297 pm x 12*

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In this book, hierarchical structures based on neural networks are investigated for automatic speech recognition. These structures are mainly evaluated within the phoneme recognition task under the Hybrid Hidden Markov Model/Artificial Neural Network (HMM/ANN) paradigm. The baseline hierarchical scheme consists of two levels each which is based on a Multilayered Perceptron (MLP). Additionally, the output of the first level is used as an input for the second level. This system can be substantially speeded up by removing the redundant information contained at the output of the first level.

General

Imprint: Springer-Verlag
Country of origin: Germany
Series: Signals and Communication Technology
Release date: November 2014
First published: 2013
Authors: Daniel Vasquez • Rainer Gruhn • Wolfgang Minker
Dimensions: 235 x 155 x 8mm (L x W x T)
Format: Paperback
Pages: 134
ISBN-13: 978-3-642-43210-1
Categories: Books > Computing & IT > Social & legal aspects of computing > Human-computer interaction
Books > Computing & IT > Applications of computing > Artificial intelligence > Natural language & machine translation
Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Applied optics > General
LSN: 3-642-43210-7
Barcode: 9783642432101

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