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Knowing that most lang id systems perform worse on short strings, I have been experimenting with normalising the length:
MIN_LEN = 30 id = langid.rank(s)[0] print langid.rank(s)[0] while len(s) < MIN_LEN: s += ' ' + s print langid.rank(s)[0] len_norm_id = langid.rank(s)[0]
I have noticed the following:
If id ie the original score was correct, the probability increases significantly after length normalisation.
If not, the probability only increases < ~10% or the identified language changes (usually to another incorrect language).
It is not a golden rule, but it is reliable enough that we could use it to:
The text was updated successfully, but these errors were encountered:
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Knowing that most lang id systems perform worse on short strings, I have been experimenting with normalising the length:
I have noticed the following:
If id ie the original score was correct, the probability increases significantly after length normalisation.
If not, the probability only increases < ~10% or the identified language changes (usually to another incorrect language).
It is not a golden rule, but it is reliable enough that we could use it to:
The text was updated successfully, but these errors were encountered: