| Hierarchical Neural Network Structures for Phoneme Recognition 2013 Edition Contributor(s): Vasquez, Daniel (Author), Gruhn, Rainer (Author), Minker, Wolfgang (Author) |
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ISBN: 3642432107 ISBN-13: 9783642432101 Publisher: Springer OUR PRICE: $104.49 Product Type: Paperback - Other Formats Published: November 2014 |
| Additional Information |
| BISAC Categories: - Technology & Engineering | Electronics - General - Computers | Natural Language Processing - Computers | User Interfaces |
| Dewey: 005.437 |
| Series: Signals and Communication Technology (Paperback) |
| Physical Information: 0.33" H x 6.14" W x 9.21" (0.49 lbs) 134 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: 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. |