Say What?
Danny Douglas N7DC
ex WN5QMX ET2US WA5UKR ET3USA
SV0WPP VS6DD N7DC/YV5 G5CTB all
DX 2-6 years each
.
QSL LOTW-buro- direct
As courtesy I upload to eQSL but if you
use that - also pls upload to LOTW
or hard card.
moderator [EMAIL PROTECTED]
moderator http://groups.yahoo.com/group/DXandTalk
----- Original Message -----
From: Robert Chudek
To: [email protected]
Sent: Sunday, April 01, 2007 11:46 AM
Subject: Re: [digitalradio] DV (Digital Voice) using PSK at 93 bps
So Leigh,
I now realize it was you that furthered your research at Rockwell Automation.
Although this video is 10-years old, it fits the timeline you suggested below.
http://emuse.ebaumsworld.com/video/watch/95
73 de Bob - KØRC in MN
----- Original Message -----
From: Leigh L Klotz, Jr.
To: [email protected]
Sent: Sunday, April 01, 2007 10:17 AM
Subject: Re: [digitalradio] DV (Digital Voice) using PSK at 93 bps
In a similar vein, in 1982, I made a speech recognition program for the
TI 99/4 home computer using a non-linear predictive algorithm to extract
parameters from the cassette tape port.
Buoyed by earlier success with a 1-bit oversampling algorithm for
recording and playback of speech, I tried parameter extraction in a
univector phase space, with a single-bit quantized value. I introduced
a primitive operator into Logo to extract this parameter using a
sample-and-hold algorithm. The algorithm sampled the cassette input
port, and held until the extracted parameter reached a "1" state, and
then returned.
The next level of decoding logic used a genetically-developed Hidden
Markov Model with a single-level probability chain. Upon return from
the sample-and-hold, the Turtle would execute the next command in
sequence, starting with "Forward 100" followed by "right 90", followed
by "clearscreen" and then "square."
In training, I would speak the commands "forward," "right",
"clearscreen," and "square." the experimental subject would then issue
the next command, which would unfortunately fail due to the lack of node
probabilities assigned to this state in the HMM. Through testing, I
found that high probability could be assigned to "clearscreen" so I
extended the HMM with a single node for clearscreen. On a hunch, I
added "square" as the terminal node.
I demonstrated the results to one of my professors, and every time I
spoke, it would execute the command flawlessly. At the end, I said,
"clearscreen," and professor nodded sagely, but with tongue in cheek.
Then he said, "Now make it draw a square again." I said "square," and
the turtle performed flawlessly, and earning me the grudging respect of
my betters.
Never underestimate the power of a Hidden Markov Model, even one with no
branches.
Leigh/WA5ZNU
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