Build a decoder that knows just the vowels are missing, and you can make a simple dictionary of all the candidate words for each compressed word. Then if you kn

Build a decoder that knows just the vowels are missing, and you can make a simple dictionary of all the candidate words for each compressed word. Then if you know the probabilities of different word pairs, you can probably pick the correct word almost all the time. The downside is that by reducing redundancy, you reduce your resilience to errors. A single typo could even propagate decoding errors to neighboring words. So maybe get fancier, and include at least one-letter errors in the list of possible words, with lower initial probabilities. One way to do this would be to use the Viterbi algorithm: https://en.wikipedia.org/wiki/Viterbi_algorithm https://en.wikipedia.org/wiki/Viterbi_algorithm