NODE c7ef5961non-cypher related question on audio analysis
jet@nas.nasa.gov (J. Eric Townsend)Mon, 19 Apr 93 15:34:26 PDT
This is only the tiniest bit related to crypto, but that doesn't seem
to be much outside the criteria for submissions to this list.. :-)
Anyone got pointers to decoding audio tones? An intro book, source
code, newsgroup, mailing list, somebody I can take to lunch? I'd like
to sample audio with my SGI, and suck out various simple tones and
combinations of tones. (DTMF, single pitch variant tones, etc.)
thx.
--
J. Eric Townsend jet@nas.nasa.gov 415.604.4311
NASA Ames Numerical Aerodynamic Simulation | play: jet@well.sf.ca.us
Parallel Systems Support, CM-5 POC | '92 R100R / DoD# 0378
PGP2.1 public key available upon request or finger jet@simeon.nas.nasa.gov
NODE 69400edfnon-cypher related question on audio analysis
Eric Hughes <hughes@soda.berkeley.edu>Thu, 22 Apr 93 10:04:16 PDT
>Anyone got pointers to decoding audio tones? An intro book, source
>code, newsgroup, mailing list, somebody I can take to lunch? I'd like
>to sample audio with my SGI, and suck out various simple tones and
>combinations of tones. (DTMF, single pitch variant tones, etc.)
I've got a good book on DSP by Rabiner and Gold.
There are a few DSP newsgroups where the local experts hang out. Also
the modem design groups.
After you know something, remember this: The FIR filter is the same
mathematically as a FFT, multiplication by a filter window function,
and an inverse FFT. As I recall, you can process multiple FIR's in
parallel.
All the DSP manufacturers come with lots of example source code for
standard filters (FFT, FIR, IIR, etc.).
Eric
NODE bcc5dcf8Re: non-cypher related question on audio analysis
Timothy Newsham <newsham@wiliki.eng.hawaii.edu>Thu, 22 Apr 93 11:42:26 PDT
>
> After you know something, remember this: The FIR filter is the same
> mathematically as a FFT, multiplication by a filter window function,
> and an inverse FFT. As I recall, you can process multiple FIR's in
> parallel.
you can do two FFT's by using the fact that:
FFT( x(t) + j y(t) ) = Z(w)
then X(l) = 1/2 ( Z(l) + Z*(N-l))
and Y(l) = 1/2j (Zl) - Z*(N-l))
Where x(t) <-> X(w)
y(t) <-> Y(w)
N is the length of both arrays
j is sqrt(-1)
Z* is the conjugate of Z (a+jb <-> a-jb )