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DM: Speech Enhancement -- Using Neural Nets?

From: anjani avasarala
Date: Wed, 20 Oct 1999 08:22:20 -0400 (EDT)

        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.

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