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Barbershop Spectrogram                                              1/10/99
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The other day, Daniel Wolf recommended a spectrogram program and I downloaded
it.  It works really well.  It seems we have reason to be happy that we live
in a time when people can trade such valuable stuff without having to bother
with value abstraction... but I digress.

To test the program, I thought I'd try some Barbershop.  For the test, I
picked a brief excerpt of song by the Happiness Emporium.  This group did
most of their recordings (including this one, from their album "That's
Entertainment!") back in the 70's, when Barbershop technique wasn't a shadow
of what it is today.  However, they have a nice sound, and I thought I'd give
them a try.

Using Cool Edit, I extracted the CD audio to 16-bit 44.1 WAV format, and
mixed it down from stereo to mono.  I then ran it thru Spectrogram, fiddling
with the settings until I got a clear picture.  The values used to produce
the image full.bmp are:

Attenuation=0
Palette=CB
Freq Scale=Log
FFT Size (points)=8192
Freq Resolution (hertz)=5.4
Band (hertz)=10-22050
Time Scale (ms)=12
Spectrum Average (ms)=1
Toggle Grid=off

This example contains a nice C7 chord, and I cropped it with Cool Edit and
spectrogrized it with the same options as above, except with a time scale of
4 milliseconds.

Note: I downsampled full.wav to 22K with Cool Edit to make it smaller for you
all.  Up.wav remains at 44K.

Note: When I save bmps with the grid on, the grid moves relative to the rest
of the graph.  This is why the bmp files on my web site don't have grids.
Does this happen to you?

Then, I opened Notepad with the idea that I'd record the frequencies of the
first 9 peaks (starting at the bottom of the graph) in this chord that I
could get a signal strength of greater than -40 dbs out of.  I picked _9_
arbitrarily.  I started at the bottom because I knew that's where most of the
parts would be.

I didn't take the readings from the same time on the graph.  Rather, I took
each reading at the strongest point in each peak (it happened that all of
these fell very near each other, in about the third quarter of the total
time).  The crosshairs have a resolution of 1cps, and I did some careful work
with the mouse.  If there was a range of frequencies that shared the same
strength, I took the one closest to the middle of the range, taking the
higher frequency if the range was odd.

After I had done all that and closed Spectrogram, I turned my text file into
the chart up.txt.  I am at a loss to explain the results.  With the transform
limited to a frequency resolution worse than 5 hertz, I should not have
gotten, nor did I expect to get, anywhere near the accuracy I did.

It may be noticed that I do not have the lead part labeled in the up.txt
chart.  At first I thought that maybe the baritone was at peak3 and the lead
at peak4, with peak2 being 5-3.  However, this would be an unusual voicing,
and listening reveals that the Baritone is singing peak2, and the lead is
singing a 5/2 above the bass.  This peak is in the spectrogram (up.bmp) but
not the chart because I couldn't get more than -40 db's out of it.