Hierarchical Neural Network Structures for Phoneme Recognition
Author | : Daniel Vasquez |
Publisher | : Springer Science & Business Media |
Total Pages | : 146 |
Release | : 2012-10-17 |
ISBN-10 | : 9783642344251 |
ISBN-13 | : 3642344259 |
Rating | : 4/5 (259 Downloads) |
Download or read book Hierarchical Neural Network Structures for Phoneme Recognition written by Daniel Vasquez and published by Springer Science & Business Media. This book was released on 2012-10-17 with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.