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audio processing

Discussion in 'Electronic Design' started by dspdspo, Jan 5, 2006.

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  1. dspdspo

    dspdspo Guest

    how do i distinguish between a recorded signal and a real time
    signal?i.e. on what basis?
  2. Pooh Bear

    Pooh Bear Guest

    Do you ? I can't see how.

  3. Follow the cable. If it comes from the recorder, it is
    carrying the recorded signal. If it goes to the microphone,
    it is the real time signal.
  4. Pooh Bear

    Pooh Bear Guest

    That'll work. ;-)

  5. Paul Burke

    Paul Burke Guest

    Let's assume that the recording wasn't made on a reel-to-reel, all-tube
    recorder with gold plated chassis, oxygen free PTFE insulated cables,
    all electrolytic caps replaced by polyester cotton, and mounted on
    vibration-proof gimbals.

    The problem then becomes easy- any hi-fi buff will INSTANTLY be able to

    Paul Burke
  6. Pooh Bear

    Pooh Bear Guest

    The current term for " hi-fi buff " is " audiophool" ( tm) J.Woodgate.

  7. Use Nyquist Sampling Theorem:

    The signal that was digitally recorded will be band-limited in its
    analogue reversion, whereas the signal that is real-time will not be
    "as band-limited". For example, assuming that the digital signal was
    sampled at 44.1kHz, you could take FT of that signal and check to see
    how much power is beyond 22.05 kHz (rougly speaking). If there is "a
    lot" of power, the signal could not have been digitally processed,
    whereas if there is essentially none, then it probably
    was....unless....the original source of the signal is Barry White, in
    which case you will not see any power above 880 Hz, whether sampled or

    Note that you have to know the sampling frequency to make this work.

    -Le Chaud Lapin-
  8. but

    maybe if you do the ol Nixongate tricks and compare the 50/60hz hum
    and see if its "genlocked" to your 50/60Hz

  9. Ben Bradley

    Ben Bradley Guest

    Be sure to digitize a good image of the source/tape switch!
  10. dspdspo

    dspdspo Guest

    you are a genius man!!
  11. ballstoall

    ballstoall Guest

    pls explain... i didn't get what you said about "a lot of power" beyond

    i mean, shouldn't there be a difference in the frequencies of recorded
    and real time?
  12. Not until you get to the cut-off frequency for a particular
    arrangement. If you look below 22.05kHz, you will see essentially
    identical images. But for frequencies above 22.05kHz, the
    straight-analogue signal will show some power (you will see a bit of
    fuzziness there on the spectral analyzer), whereas for the digitally
    processed signal, you will see a drop-to-zero. Here's what's

    If you take the straight-analogue signal, and view its spectral
    content, you will most likely see components in the lower frequences
    (under 20kHz), as well as components at higher frequencies (above

    If you look at the recorded signal, assuming that the spectral content
    of whatever was recorded also had frequency components higher than
    20kHz, you will *not* see those higher components in the analogue
    output of the digitally processed signal. The reason has to do with
    filtering. To reconstruct an analogue signal perfectly, the rate of
    sampling must be at least twice the highest frequency component
    contained in the sampled signal. So if someone plays high-pitched
    music, and the highest frequency component in that music is 8 kHz, then
    one must operate the A/D converter at at least 16 kilosamples per
    second (kps) for perfect reconstruction which is equivalent to avoiding
    spectral overlap in the frequency domain. This is the essence of the
    Nyquist Sampling Theorem, and this theorem is directly related to what
    is really happing when you sample a signal and later convert it back to
    analog - when you sample the signal in the time domain, with the
    *intent* to regenerate the analogue signal, you should think in your
    mind, at each instant of sample, BAM!!! You are multiplying the signal
    with a sequence of impulses, where each impulse is a BAM! Then, to see
    what this combination of multiplied signals makes in the frequency
    domain, you must convolve the image of the sampled signal in the
    frequency domain with the Fourier Transform of the "BAM" signals,
    which, in the frequency domain, is yet another train of impulses, but
    scaled by a factor. To keep the resulting blobs from overlapping each
    other, the spacing between the impulses in the time domain must be very
    narrow, or equivalently, very wide in the frequency domain. But "very
    wide" is relative - if a signal is sufficiently band-limited for a
    particular spacing of the impulse train in the frequency domain, then
    no overlap will occur during convolution. To band-limit the signal,
    you must use an anti-aliasing (low-pass) filter before sampling to kill
    off any frequencies higher than 22.05 kHz, and another similar filter
    at the output.

    So if you are listening to a signal that is analogue throughout the
    channel, it *could* have components higher than 22.05kHz. But if
    you're listening to a signal that has been low-pass filtered, digitally
    sampled (A/D), converted back to analog (D/A), and low-pass filtered
    again, you can be certain that components above 22.1kHz have been
    essentially killed off. For a digitally processed signal, anything
    beyond 22.05kHz will be due to noise and imperfections in the output
    filter itself, and should barely show up on a spectral analyzer.

    It should come as no suprise to you that 22.05 kHz (44.1 ksps) is the
    cut-off frequency. It just happens to be near the threshold of hearing
    for many humans.

    -Le Chaud Lapin-
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