Hierarchical Neural Network Structures for Phoneme Recognition
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
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.
109.99
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Hierarchical Neural Network Structures for Phoneme Recognition
134
Hierarchical Neural Network Structures for Phoneme Recognition
134
109.99
In Stock
Product Details
| ISBN-13: | 9783642344244 |
|---|---|
| Publisher: | Springer Berlin Heidelberg |
| Publication date: | 10/18/2012 |
| Series: | Signals and Communication Technology |
| Edition description: | 2013 |
| Pages: | 134 |
| Product dimensions: | 6.10(w) x 9.25(h) x (d) |
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