Neural Network can't recognize some utterances

Neural Network can't recognize some utterances

Post by E. Ess » Fri, 24 Aug 2007 17:57:19


I'm working on speech recogntion using some kind of neural networks.

I'm trying LVQ function in matlab Newlvq for 300 utterance (10 words,
10 speaker,3 repetition) for training and the same for test.

The problem is in testing the function sim may produce empty matrix
for one or more utterance , they can't recognize the utterance at
all , as we know neural try to find the nearest class for the
utterance , but in many cases it causes empty matrix.

What's the problem ? How can overcome this?

Thanks in advance

1. Neural Network can't recognize some utterances

2. Neural Network Architecture with MATLAB Neural Network Toolbox

Dear neural network experts,
I would like to make a neural network model for a situation
when some of the input variables can interact, while
others don't have any interactions. This information is
based on logical considerations and I have to include it
into the architecture of the net.
For example, I have 3 different groups of input variables.
Within each groups the variables are disjunct (i.e. no
interaction). Variables of different groups may interact.
This would result in either
- restrictions to some weights of a network consisting of
completely inter-linked neurons (i.e. some weights have
to be zero), or
- a combination of neural networks, one for each group of
variables and one combining the groups (nested nets?).

This network needs to be created, trained and simulated.
How can I implement this based on commands of the neural network
toolbox (newff?, trainlm?)?

I would be very happy if you can point me to an example or
similar that demonstrates how the commands have to be used
in this situation.

Many thanks in advance!

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