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Hierarchical Neural Network Structures for Phoneme Recognition

Hierarchical Neural Network Structures for Phoneme Recognition

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Signals and Communication Technology

Hierarchical Neural Network Structures for Phoneme Recognition

Daniel Vasquez | Rainer Gruhn | Wolfgang Minker

Technology & Engineering / Signals & Signal Processing

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.

Publication Date: 18 October 2012
Publisher: Springer Berlin Heidelberg
Imprint: Springer
ISBN-13: 9783642344244
Format: Hardback
Page Count: 134

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