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Hierarchical Neural Network Structures for Phoneme Recognition

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Hierarchical Neural Network Structures for Phoneme Recognition Synopsis

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.

About This Edition

ISBN: 9783642432101
Publication date:
Author: Daniel Vasquez, Rainer Gruhn, Wolfgang Minker
Publisher: Springer an imprint of Springer Berlin Heidelberg
Format: Paperback
Pagination: 134 pages
Series: Signals and Communication Technology
Genres: Electronics engineering
Natural language and machine translation
Digital signal processing (DSP)
Human–computer interaction
Artificial intelligence