![]() ![]() People are also less helpful or patient when asking for unknown words or explanations. What people forget is that adults do not get exposed to the same basic level of interactions that kids do. ![]() Posted in Machine Learning Tagged cnn, CTC, cw, lstm, machine learning, morse, SNR, tensorflow Post navigation We find that fascinating, and wonder what other applications this would be good for. By comparing patterns to labels in the training data, it inferred what the characters mean, and essentially taught itself Morse code in about an hour. Other Morse decoders use lookup tables to convert sound to text, but it’s important to note that this one doesn’t. The model was also able to pull Morse out of a signal with -6 dB signal-to-noise ratio, even though it had been trained with a much cleaner signal. The first training run only resulted in about 36% accuracy, but a subsequent run with shorter snippets ended up being 99.5% accurate. Using a few lines of Python, he converts short, known snippets of Morse to a grayscale image that looks a little like a barcode, with the light areas being the dits and dahs and the dark bars being silence. But things take an unexpected turn right from the start, as uses a Tensorflow handwriting recognition implementation to train his model. His method uses curated training data to build a model, namely Morse snippets and their translations, as is the usual approach with such systems. The blog entry by the delightfully callsigned reads like a scientific paper, with good reason: really seems to know a thing or two about machine learning. Militaries use immersion language instruction, as do diplomats and journalists, and apparently computers can now use it to teach themselves Morse code. If you've read this far, you may be interested in the older version of this tool which does not attempt to adapt to the sound and also includes more diagnostic information.Conventional wisdom holds that the best way to learn a new language is immersion: just throw someone into a situation where they have no choice, and they’ll learn by context. The volume threshold is the value (0-255) which the measured volume in the analysed frequency must exceed to be counted as a dit or dah. The volume filter (which uses dB) discards very quiet (very negative) or very loud (close to zero) sounds and scales the size of the remaining data. There are three parameters which are not automatic: the minimum and maximum volume filter settings and the volume threshold setting. The frequency can only be certain values and the closest allowed value will be chosen. ![]() If you want to fix the frequency or speed then click on the "Manual" checkboxes and type in your chosen values. ![]() In fully automatic mode, the decoder selects the loudest frequency and adjusts the Morse code speed to fit the data. From these timings it determines if something is a dit, dah, or a sort of space and then converts it into a letter shown in the message box. If the volume in the chosen frequency is louder than the "Volume threshold" then it is treated as being part of a dit or dah, and otherwise it records a gap (this is shown in the lower graph that looks like a barcode). The spectrogram of the sound is shown in the main graph along with a pink region showing the frequency being analysed. The decoder will analyse sound coming from the microphone or from an audio file. ![]()
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