Hierarchical Neural Network Structures for Phoneme Recognition (Paperback)

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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