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Example of calculating the probability of a word, from character probabilities
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# A python example of calculating the probability of the word 'hine' | |
# See https://discourse.mozilla.org/t/quick-heads-up-on-some-metadata-confidence-estimate-work-were-doing/40618/2 | |
# The probability that a word is incorrect before the nth letter: | |
def p_not_word(n, probabilities): | |
if n == 0: | |
return 0 | |
else: | |
return probabilities[n - 1] * p_not_word(n - 1, probabilities) + \ | |
(1 - probabilities[n - 1]) | |
# The probability of a word being correctly emitted, given the character | |
# probabilities: | |
def p_word(probabilities): | |
return 1 - p_not_word(len(probabilities), probabilities) | |
# Character probabilities for the word 'hine' (including the following space): | |
# h i n e blank | |
hine = [0.994121, 0.998789, 0.999938, 0.998212, 0.841081] | |
# The probability of the word 'hine', assuming independent draws with those | |
# probabilities, following the probability tree: | |
p_hine = 1 - ( | |
(1 - 0.994121) + # not h | |
0.994121 * (1 - 0.998789) + # h * not i | |
0.994121 * 0.998789 * (1 - 0.999938) + # h * i * not n | |
0.994121 * 0.998789 * 0.999938 * (1 - 0.998212) + # h * i * n * not e | |
0.994121 * 0.998789 * 0.999938 * 0.998212 * (1 - 0.841081) # h * i * n * e * not space | |
) | |
# Check the manual and the recursive calculation are the same | |
assert round(p_hine, 5) == round(p_word(hine), 5), \ | |
'Error in the calculation of word probabilities' | |
# And here is the probability of the word 'hine' (0.83357883745) | |
print(p_word(hine)) | |
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