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Image of book cover for Hierarchical Neural Network Structures for Phoneme Recognition

Hierarchical Neural Network Structures for Phoneme Recognition

Daniel Vasquez, Rainer Gruhn, and Wolfgang Minker
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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.

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Hierarchical Neural Network Structures for Phoneme Recognition (Signals and Communication Technology)
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Length: 146 pages
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