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Author Topic: Wetware vs. AI Software - Pursuit of Ultimate Morse Decoder  (Read 41558 times)
AG1LE
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« on: September 22, 2013, 10:46:29 PM »

Back in June I presented some of my work related to Morse Code decoders at an event organized by New England Artificial Intelligence group.
Some 70+ people participated including couple hams.  We had some good conversations after the presentation. More details and presentation slides are in here:  http://www.meetup.com/intelligence/events/119478492/. There is also a youtube video recorded from the event:  http://www.youtube.com/watch?v=ckjo-xw-s0w

I tried to highlight the huge gap there is between best human CW capabilities vs. computers running AI / machine learning algorithms.
This is probably nothing new to the active readers of this forum but the audience in above event seemed genuinely interested in solving the Morse decoding problem(s) and had some great suggestions.

I have been working on a new CW decoder that combines Bayesian approach with probabilistic models of channel fading, speed transition, timing variation, Morse and letter transitions. This software builds a trellis of alternative decoding paths sorted by probability, taking into account  calculated conditional probabilities. While there is a lot of computation done for each 5 ms sample, this approach seems quite promising in terms of decoding accuracy. Once I get some more test cases done I can publish the first results. The software is currently a standalone C program but could be easily integrated to other software like FLDIGI. Let me know if you are interested in this.       

73
Mauri AG1LE
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N0IU
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« Reply #1 on: September 23, 2013, 04:19:54 AM »

In the time it would take to write a program that could come anywhere close to human capabilities, you could learn Morse code yourself!  Cheesy
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W1JKA
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« Reply #2 on: September 23, 2013, 06:38:10 AM »

Re: N0IU

    What you said is true, but consider that once the program IS written how much easier it would be for the non handicapped instant no code multiple guess amateur extra licensed hams with their out of the box appliance shacks to use their push button fingers in the CW mode and help keep the this ancient mode alive. Wink
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AG1LE
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« Reply #3 on: September 23, 2013, 06:58:11 AM »

In the time it would take to write a program that could come anywhere close to human capabilities, you could learn Morse code yourself!  Cheesy
Scott

Listening ( & replaying) captured CW audio clips where the software has particular problems adapting to speed changes or some other issues has already improved my rusty CW copying skills.
I agree that spending more time on band could be faster way to learn but this project has helped me also to gain better understanding on machine learning / AI algorithms. There has been tremendous progress made in machine learning systems in the last 5 - 10 years - just think about "self driving cars"  or  "autonomous robots" like Mars rover. Some of these algorithms are available as open source for anybody to apply to another problem, such as Morse decoding. 

Part of attractiveness of ham radio is experimentation with new technologies, right?  This problem is not too difficult for a single individual to make some progress and learn by doing.
The nice side benefit is improving my own personal CW copying skills. And perhaps some other hams could find some use for the software as well?

73
Mauri     
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WX2S
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« Reply #4 on: September 23, 2013, 07:53:22 AM »

Quote from: Siri
I have no doubt that with sufficient effort and AI Morse code decoder will be in human alive. It's already happened with Chesson Jeffrey. By the way, I'm voicing this in with Siri, and you can see some of the aftereffects.

Translation:

I have no doubt that with sufficient effort an AI Morse code decoder will beat any human alive. It's already happened with Chess and Jeopardy. By the way, I'm voicing this in with Siri, and you can see some of the aftereffects.  Grin

73,
Wx2s.
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73, - Steve WX2S.
I subscribe to the DX Code of Conduct. http://dx-code.org/
N0IU
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« Reply #5 on: September 23, 2013, 09:26:25 AM »

Mauri,

As someone who came up through the ranks "back in the day", I was really just giving you a hard time about developing a machine-based system that you could CW as well as an experienced operator. (That's why I put the smiley face on there!) I can certainly appreciate the fact that this is not only an amateur radio pursuit as much as it is an academic pursuit to try and see just how far AI can take us.
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K9MRD
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« Reply #6 on: September 23, 2013, 10:14:22 AM »

Mauri,

I have been a ham for 55 years and spend about 90% of my time on CW.   I would appreciate reading updates about this project.

Wayne
K9mrd
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N3QE
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« Reply #7 on: September 23, 2013, 10:36:37 AM »

The standard of comparison here, would be CW Skimmer.

In general I don't think the tools have to be as good as a trained human at single channel decoding. But at full-spectrum decoding... wow CW Skimmer is a powerful tool.

Very nice video of CW Skimmer from a cold start in a 160 test: http://www.youtube.com/watch?v=ZarmnghuQK8
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KC8Y
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« Reply #8 on: September 23, 2013, 03:16:51 PM »

I would like to see "CW Skimmer."

What is the website (URL) for the download Huh
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KC8Y
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« Reply #9 on: September 23, 2013, 04:23:51 PM »

Found it Smiley
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GILGSN
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« Reply #10 on: September 23, 2013, 08:13:14 PM »

If you can make it fit in an Arduino board...

Gil.
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NI0C
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« Reply #11 on: September 23, 2013, 08:57:04 PM »

Mauri,
In another thread, you mentioned you were interested in some comparisons between your software and human decoding.  When you develop some relevant sound files, please share them with us; I'll see what I can do with them (in the spirit of John Henry, Johnny cash's "steel drivin' man").
73,
Chuck  NI0C
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KC8IIR
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« Reply #12 on: September 24, 2013, 03:03:01 AM »

Everyone knows this stuff works in all emergency situations. No worries. Trust the software.



Greg kc8iir
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AG1LE
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« Reply #13 on: September 27, 2013, 05:13:43 PM »

Mauri,
In another thread, you mentioned you were interested in some comparisons between your software and human decoding.  When you develop some relevant sound files, please share them with us; I'll see what I can do with them (in the spirit of John Henry, Johnny cash's "steel drivin' man").
73,
Chuck  NI0C

Hi Chuck

I posted some sound files with -10 dB to +20 dB SNR @ 2kHz BW.  See my latest blog post on CER vs. SNR testing http://ag1le.blogspot.com/2013/09/new-morse-decoder-part-1.html.  The sound files are here: https://www.dropbox.com/sh/2j9chxsizxjeqgp/Gj97asYzpW.

73
Mauri AG1LE
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AG1LE
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« Reply #14 on: September 27, 2013, 05:27:15 PM »

If you can make it fit in an Arduino board...

Gil.
Gil
I don't have an Arduino board but the software is posted in Github: https://github.com/ag1le/morse-wip.
It has currently about 3335 lines of code and has some F2C library dependencies that I am planning to remove.
It also requires a lot of cleanup work but I got it working the other night. First test results are here: http://ag1le.blogspot.com/2013/09/new-morse-decoder-part-1.html

If you have time and energy perhaps this algorithm can be packaged to fit in Arduino footprint? 

73
Mauri AG1LE
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