Speech Recognition Using Neural Network | Project

Running head: SPEECH RECOGNITION USING SHALLOW NEURAL NETWORK
CLASSIFICATION
Speech Recognition Using Shallow Neural Network Classification
Student’s name
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SPEECH RECOGNITION USING SHALLOW NEURAL NETWORK CLASSIFICATION
Table of Contents
Abstract............................................................................................................................................2
Introduction......................................................................................................................................3
Problem definition...........................................................................................................................3
Methodology....................................................................................................................................3
Experiments and discussion.............................................................................................................4
Bayesian regularization algorithm...................................................................................................5
Matlab..............................................................................................................................................5
Neural network architecture............................................................................................................6
Network training summary..............................................................................................................7
A plot of training state.....................................................................................................................7
Error histogram for test set..............................................................................................................8
Roc plot for test classes...................................................................................................................8
A plot of the confusion matrix.........................................................................................................9
Conclusion.....................................................................................................................................10
References......................................................................................................................................11
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SPEECH RECOGNITION USING SHALLOW NEURAL NETWORK CLASSIFICATION
Abstract
Speech recognition is a technology used by human beings to identify and capture the
voice spoken through the microphone. The words or the voice is then decoded by a speech
recognizer, which in system outputs the recognized words. Speech recognition technology offers
a platform for better recognition of the voice even when there is a lot of noise.
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SPEECH RECOGNITION USING SHALLOW NEURAL NETWORK CLASSIFICATION
Introduction
This project aims to come up with a system that will have a higher recognition accuracy
and, at the same time, reducing the time taken in the recognition process(Youhao, 2012). The
improved noise-robust features will ensure that there are accuracy and better extraction
capabilities. Once this project is complete, it can be used to perform a variety of technical
services that may include the use of voice for security purposes, in dialing applications, and even
in application control systems (Arora & Singh, 2012). For disabled people, speech recognition
applications can help them in enhancing their communication capabilities. It will also help
people with spinal cord injuries to access private areas with the use of a voice recognition
program (Gevaert, Tsenov, & Mladenov, 2010). The program should be in a position to interpret
voice command with the use of computer-based systems.
Problem definition
Speech recognition aids persons who are disabled. Speech recognition has also been
applied to enhancing security. Even though the project may be expensive, it will provide the
necessary assistance to many people and at the same time enhancing security. The program will
be in a position to offer different kinds of speech recognition, including isolation speech,
connected speech, and spontaneous speech.
Methodology
A shallow neural network methodology will be used to classify the data to be used as
input in speech recognition. Shallow neural networks are network architectures that have only
one hidden layer as opposed to a deep neural network that contains several hidden strata (Wang,
Jiang, & Xie, 2017). The use of Bayesian regularization algorithms improves the level of
accuracy in speech recognition because it operates on a logarithmic scale. The Bayesian
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