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DM: Speech Enhancement -- Using Neural Nets?From: anjani avasarala Date: Wed, 20 Oct 1999 08:22:20 -0400 (EDT)
Hello,
can anyone help me in tacking the below problem?.
I am working on speech enhancement.
We are trying to address the issue of speech enhancement
when the speech is degraded by two ways:
1. Additive noise
2. This case needs a brief introduction:
The situation is like this. The speech signal is
encoded using a standard coding technique (say
Continuously variable slope delta modulation (CVSD)).
So all we have is now a binary bit pattern. If this
is all, there is no problem. We can apply corresponding
decoding technique to get back the signal. But now some
bits in this coded speech are flipped (the choice of bits
is at random). So, the sequence information is lost.
In such cases we would like to do the following studies:
(a) Is there any way to reconstruct the speech signal from
this new binary pattern ( i.e., flipped coded speech)?
(b) What features of the original speech signal does this
new signal retain?
This problem can be looked in two different ways:
1. Applying bit error correction codes. But this
methods doesn't take into account the speech concepts.
2. Another method is exploiting the redundancy in the
speech signal. As we know speech is highly redundant
in nature. So, it is not necessary to know each and
every word to infer the message. So, does coded speech
still contain this redundancy?. If so, what happens when
bits are flipped at random?.
Can neural networks be useful in this context?.
Currently, I am working on neural network methods only.
Hope I am clear. Write to me for further details.
Hope someone will respond to this.
Thankyou,
Anjani
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