Automatic text normalisation
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- Diacritic restoration
- Reduplicated character reduction
- How to learn language specific settings? -- e.g. in English certain consonants can double, but others cannot, same goes for vowels. Can we learn these by looking at a corpus ?
- For the language subpart... we can actually train and keep copies of most frequently corrected words across languages and then refer to that list...
- Maybe this will be too heavy for the on the run application ( needs discussion )
To do list
- Feed charlifter with n-grams ( works best with a trigram model ). This would improve the diacritics at the moment
- Make list of most frequently occurring non dictionary words, these might be abbreviations..
- add most frequently occuring english abbreviations to the list