.: Click here to download :.
Neural networks emerged as an attractive acoustic modeling approach in ASR in the late 1980s. Since then, neural networks have been used in
many aspects of speech recognition such as phoneme classification, isolated word recognition, and speaker adaptation.
In contrast to HMMs, neural networks make no assumptions about feature statistical properties and have several qualities making them attractive
recognition models for speech recognition. When used to estimate the probabilities of a speech feature segment, neural networks allow discriminative
training in a natural and efficient manner. Few assumptions on the statistics of input features are made with neural networks.
Index Terms: Matlab, source, code, speech, recognition, isolated, word, words, feature, neural, network, networks, ANN.
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Figure 1. Neural network architecture |
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A simple and effective source code for Neural Network Speech Recognition System. |
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Demo code (protected
P-files) available for performance evaluation. Matlab Signal Processing Toolbox is required. |
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Release |
Date |
Major features |
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1.0 |
2014.01.05 |
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We recommend to check the secure connection to PayPal, in order to avoid any fraud. This donation has to be considered an encouragement to improve the code itself. |
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Neural Network Speech Recognition System - Click here for
your donation. In order to obtain the source code you
have to pay a little sum of money: 90 EUROS (less
than 126 U.S. Dollars). |
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Once you have done this, please email us luigi.rosa@tiscali.it As soon as possible (in a few days) you will receive our new release of Neural Network Speech Recognition System. Alternatively, you can bestow using our banking coordinates:
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The authors have no relationship or partnership
with The Mathworks. All the code provided is written in Matlab
language (M-files and/or M-functions), with no dll or other
protected parts of code (P-files or executables). The code was
developed with Matlab 2006a. Matlab Signal Processing Toolbox is required.
The code provided has to be considered "as is" and it is without any kind of warranty. The
authors deny any kind of warranty concerning the code as well
as any kind of responsibility for problems and damages which may
be caused by the use of the code itself including all parts of
the source code.
