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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Hierarchical Neural Network Structures for Phoneme Recognition

Hierarchical Neural Network Structures for Phoneme Recognition

Gruhn, Rainer
Minker, Wolfgang
Vasquez, Daniel

Hardcover

Series: Signals and Communication Technology

Technology & EngineeringGeneral Computers

ISBN10: 3642344240
ISBN13: 9783642344244
Publisher: Springer
Published: Oct 18 2012
Pages: 134
Weight: 0.80
Height: 0.60 Width: 6.30 Depth: 9.20
Language: English
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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