FastWER
A PyPI package for fast word/character error rate (WER/CER) calculation
- fast (cpp implementation)
- sentence-level and corpus-level WER/CER scores
- Unicode code point-based character error rates
Installation
pip install fastwer
Example
import fastwer
hypo = ['This is an example .', 'This is another example .']
ref = ['This is the example :)', 'That is the example .']
# Corpus-Level WER: 40.0
fastwer.score(hypo, ref)
# Corpus-Level CER: 25.5814
fastwer.score(hypo, ref, char_level=True)
# Sentence-Level WER: 40.0
fastwer.score_sent(hypo[0], ref[0])
# Sentence-Level CER: 22.7273
fastwer.score_sent(hypo[0], ref[0], char_level=True)
Character-level scoring treats each Unicode code point as one character. Normalize text before scoring if canonically equivalent representations, such as composed and decomposed accented characters, should compare as equal.
Contact
Changhan Wang (wangchanghan@gmail.com)
1 maintainer
Metadata
1 maintainer
Release files for fastwer 0.2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| fastwer-0.2.0.tar.gz | 7.0 kB | With provenance | Details |
Built distributions (wheels)
Total release size: 34.9 MB
Release files / fastwer-0.2.0.tar.gz
| Download URL | fastwer-0.2.0.tar.gz |
|---|---|
| Size | 7.0 kB |
| Tags | Source |
|
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| Download URL | fastwer-0.2.0-cp313-cp313-win_amd64.whl |
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| Size | 270.7 kB |
| Tags | CPython 3.13 Windows x86-64 |
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| Download URL | fastwer-0.2.0-cp313-cp313-musllinux_1_2_x86_64.whl |
|---|---|
| Size | 2.2 MB |
| Tags | CPython 3.13 Linux musl 1.2+ x86-64 |
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| Size | 2.1 MB |
| Tags | CPython 3.13 Linux musl 1.2+ ARM64 |
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| Tags | CPython 3.12 Linux musl 1.2+ x86-64 |
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| Size | 2.1 MB |
| Tags | CPython 3.12 Linux musl 1.2+ ARM64 |
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