Trevor Smithers wrote:
What you really need is a method of identifying the actual ssb speech waveform, extracting the noise
More or less by definition, if you have mix of an unknown signal and
noise, you cannot separate the two. That's because noise is random and
therefore unpredictable and the signal is unknown, so also unpredictable.
To remove some of the noise, you must make assumptions about the signal.
For speech, that probably means assuming that only discrete formant
frequencies are present (but that isn't valid for unvoiced sounds and
particularly for s and h sounds - the loss of these may be why people
find noise reduced signals to be muddy), identify those frequencies, and
then attenuate all the other frequencies.
If the signal is close to the noise, you will not be able to identify
the important frequencies properly, and therefore not be able reduce the
noise this way.
More drastically, you can try and construct a set of voice tract model
parameters, and then synthesize the speech from those (this is what GSM
does, but for bandwidth reduction rather than noise reduction, so it
assumes a reasonable starting SNR).
Most drastically, you use speech recognition and have the noise reducer
re-speak the words. Currently the best tool for doing speech
recognition in the presence of noise is the human brain, though, so the
best way of getting noise reduction is to get someone else to listen to
the signal and repeat it to you!
Generally, noise reduction has to be more of an operator comfort thing
than really improving the signal. If the noise is so strong that you
cannot make out the speech, the noise reduction isn't going to be able
to find it anyway.
--
David Woolley
Emails are not formal business letters, whatever businesses may want.
RFC1855 says there should be an address here, but, in a world of spam,
that is no longer good advice, as archive address hiding may not work.
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