Hierarchical Neural Network Structures for Phoneme Recognition (Signals and Communication Technology)

Vasquez, Daniel/ Gruhn, Rainer/ Minker, Wolfgang

Springer-Verlag Berlin and Heidelberg GmbH & Co. K（2014/11発売）

• 製本 Paperback:紙装版/ペーパーバック版／ページ数 134 p.
• 言語 ENG
• 商品コード 9783642432101

Full 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.

Contents

Background in Speech Recognition.- Phoneme Recognition Task.- Hierarchical Approach and Downsampling Schemes.- Extending the Hierarchical Scheme: Inter and Intra Phonetic Information.- Theoretical framework for phoneme recognition analysis.