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What many other Morse trainers use is canned QSO-style templates with placeholders for name / rig / etc. This works but quickly gets repetitive.
We'd ideally have something like a Markov chain (or one of the newfangled char-rnn type text generators) trained on a bunch of both natural text and QSOs. Such a model would be relatively compact yet generate endless amounts of novel text to practice with. The main issue would be getting enough real QSO text for training.
The text was updated successfully, but these errors were encountered:
Right now it's just a random selection of words.
What many other Morse trainers use is canned QSO-style templates with placeholders for name / rig / etc. This works but quickly gets repetitive.
We'd ideally have something like a Markov chain (or one of the newfangled char-rnn type text generators) trained on a bunch of both natural text and QSOs. Such a model would be relatively compact yet generate endless amounts of novel text to practice with. The main issue would be getting enough real QSO text for training.
The text was updated successfully, but these errors were encountered: