Comments (2)
I think there are two ways of implementing this:
- we need a either wrap around asclite which will require shipping its binary for every platform
- or write a custom dynamic programming solution, which would be most likely be very slow if implemented in python, or difficult if it needs to be written in C (I don't have much if any experience in writing C and integrating it into a python application).
How would you use this feature? Are there many speech datasets which have this problem?
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Thanks for your answer.
How would you use this feature? Are there many speech datasets which have this problem?
All datasets that include overlapping speech have this problem. Few examples: Chime5-6, AMI, wsj0-mix, Librimix. In order to evaluate speech separation algorithm, this seems to be needed.
I'd go with solution 1.
I personally wouldn't ship the binaries but link to the installation instructions. This would be an optional feature of jiwer
, and the user would need to make an extra step to benefit from it. WDYT?
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Related Issues (20)
- Don't support Chinese? HOT 4
- AttributeError: module 'jiwer' has no attribute 'cer'
- SentencesToListOfWords is removed after 2.2.0 HOT 8
- RemovePunctuation does not remove smart/curly quotes HOT 2
- Avoid error when a string in the truth is empty after transformation HOT 2
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- Batch vs Individual results are not same HOT 6
- Update Levenshtein dependency to maintained version
- Major performance regression in 2.5.0 for jiwer.transforms.RemovePunctuation HOT 2
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- Current licenses might not be allowed HOT 2
- jiwer.visualize_measures doesn't work as in the docs HOT 2
- Version 3.0.0 can produce wrong results HOT 1
- Regarding visualize_alignment() function. HOT 1
- Apparent WER bug? HOT 2
- Update rapidfuzz version HOT 1
- jiwer gives an error when passed a very long list of strings HOT 6
- Can't
- jiwer.wer(outputs_true, outputs_pred, standardize=True) HOT 1
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