Skip to content
Closed
Show file tree
Hide file tree
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
14 changes: 7 additions & 7 deletions metrics/cer/cer.py
Original file line number Diff line number Diff line change
Expand Up @@ -137,23 +137,23 @@ def _info(self):

def _compute(self, predictions, references, concatenate_texts=False):
if concatenate_texts:
return jiwer.compute_measures(
return jiwer.process_words(
references,
predictions,
truth_transform=cer_transform,
reference_transform=cer_transform,
hypothesis_transform=cer_transform,
)["wer"]
).wer

incorrect = 0
total = 0
for prediction, reference in zip(predictions, references):
measures = jiwer.compute_measures(
out = jiwer.process_words(
reference,
prediction,
truth_transform=cer_transform,
reference_transform=cer_transform,
hypothesis_transform=cer_transform,
)
incorrect += measures["substitutions"] + measures["deletions"] + measures["insertions"]
total += measures["substitutions"] + measures["deletions"] + measures["hits"]
incorrect += out.substitutions + out.deletions + out.insertions
total += out.substitutions + out.deletions + out.hits

return incorrect / total
10 changes: 5 additions & 5 deletions metrics/wer/wer.py
Original file line number Diff line number Diff line change
Expand Up @@ -14,7 +14,7 @@
""" Word Error Ratio (WER) metric. """

import datasets
from jiwer import compute_measures
from jiwer import process_words

import evaluate

Expand Down Expand Up @@ -95,12 +95,12 @@ def _info(self):

def _compute(self, predictions=None, references=None, concatenate_texts=False):
if concatenate_texts:
return compute_measures(references, predictions)["wer"]
return process_words(references, predictions).wer
else:
incorrect = 0
total = 0
for prediction, reference in zip(predictions, references):
measures = compute_measures(reference, prediction)
incorrect += measures["substitutions"] + measures["deletions"] + measures["insertions"]
total += measures["substitutions"] + measures["deletions"] + measures["hits"]
out = process_words(reference, prediction)
incorrect += out.substitutions + out.deletions + out.insertions
total += out.substitutions + out.deletions + out.hits
return incorrect / total