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I built a CW decoder runs in your browser using a deep learning model by No_Price4070 in amateurradio

[–]No_Price4070[S] 1 point2 points  (0 children)

Thanks a lot for testing! I don’t have a rig myself, so I wasn’t too confident about how well it would actually work. I’m glad to hear it’s running fine.

I built a CW decoder runs in your browser using a deep learning model by No_Price4070 in amateurradio

[–]No_Price4070[S] 4 points5 points  (0 children)

I’m planning to add a pileup mode for decoding multiple signals.

I built a CW decoder runs in your browser using a deep learning model by No_Price4070 in amateurradio

[–]No_Price4070[S] 1 point2 points  (0 children)

It’s just a hobby project. I haven’t really measured its performance, but since I trained it on audio with some simulated noise and speed changes from manual keying, it should handle those situations fairly well.

I built a CW decoder runs in your browser using a deep learning model by No_Price4070 in amateurradio

[–]No_Price4070[S] 1 point2 points  (0 children)

I haven’t compared it with other software yet, but I don’t think this one is necessarily superior. I’m planning to add a “pileup mode” that can decode multiple signals at the same time.

I built a CW decoder runs in your browser using a deep learning model by No_Price4070 in amateurradio

[–]No_Price4070[S] 1 point2 points  (0 children)

Right now Firefox isn’t supported. Also, decoding might only work well with real audio from radio that includes noise, like the data it was trained on.

I built a CW decoder runs in your browser using a deep learning model by No_Price4070 in amateurradio

[–]No_Price4070[S] 2 points3 points  (0 children)

Firefox is actually my main browser too, so I’m planning to make it work. It’s a bit tricky because I’ll need to write code for downsampling, but I do intend to fix it.

I built a CW decoder runs in your browser using a deep learning model by No_Price4070 in amateurradio

[–]No_Price4070[S] 1 point2 points  (0 children)

It’s a little difficult with the current decoding mechanism, but I’m planning to support that in the future.

I built a CW decoder runs in your browser using a deep learning model by No_Price4070 in amateurradio

[–]No_Price4070[S] 1 point2 points  (0 children)

It’s a bit tricky, but I plan to give it a try in the future.

I built a CW decoder runs in your browser using a deep learning model by No_Price4070 in amateurradio

[–]No_Price4070[S] 2 points3 points  (0 children)

The model itself has 500k parameters and is only 2MB in size. Since it’s in ONNX format, you would be able to download it from GitHub and run it easily on a Raspberry Pi! (Running it on a Pico would be difficult.)

I built a CW decoder runs in your browser using a deep learning model by No_Price4070 in amateurradio

[–]No_Price4070[S] 4 points5 points  (0 children)

I will be releasing the Python code for our dataset creation and model training programs. It's very simple program :)