Hierarchical Neural Network Structures for Phoneme Recognition (Hardcover, 2013 ed.)

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:	October 2012
First published:	2013
Authors:	Daniel Vasquez • Rainer Gruhn • Wolfgang Minker
Dimensions:	235 x 155 x 15mm (L x W x T)
Format:	Hardcover
Pages:	134
Edition:	2013 ed.
ISBN-13:	978-3-642-34424-4
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:	3-642-34424-0
Barcode:	9783642344244

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