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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.
| Autorius: | Daniel Vasquez, Wolfgang Minker, Rainer Gruhn, |
| Serija: | Signals and Communication Technology |
| Leidėjas: | Springer Berlin Heidelberg |
| Išleidimo metai: | 2014 |
| Knygos puslapių skaičius: | 152 |
| ISBN-10: | 3642432107 |
| ISBN-13: | 9783642432101 |
| Formatas: | 235 x 155 x 9 mm. Knyga minkštu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Hierarchical Neural Network Structures for Phoneme Recognition“
