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@@ -0,0 +1 @@ +/jiwer-3.0.1.tar.gz diff --git a/python-jiwer.spec b/python-jiwer.spec new file mode 100644 index 0000000..10f2b76 --- /dev/null +++ b/python-jiwer.spec @@ -0,0 +1,239 @@ +%global _empty_manifest_terminate_build 0 +Name: python-jiwer +Version: 3.0.1 +Release: 1 +Summary: Evaluate your speech-to-text system with similarity measures such as word error rate (WER) +License: Apache-2.0 +URL: https://github.com/jitsi/jiwer +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/96/b1/ebacdf7d82d92d3ab93bdaf9f0657782e59cf734ad336e331a8806f2bbf7/jiwer-3.0.1.tar.gz +BuildArch: noarch + +Requires: python3-rapidfuzz +Requires: python3-click + +%description +# JiWER + +JiWER is a simple and fast python package to evaluate an automatic speech recognition system. +It supports the following measures: + +1. word error rate (WER) +2. match error rate (MER) +3. word information lost (WIL) +4. word information preserved (WIP) +5. character error rate (CER) + +These measures are computed with the use of the minimum-edit distance between one or more reference and hypothesis sentences. +The minimum-edit distance is calculated using [RapidFuzz](https://github.com/maxbachmann/RapidFuzz), which uses C++ under the hood, and is therefore faster than a pure python implementation. + +## Documentation + +For further info, see the documentation at [jitsi.github.io/jiwer](https://jitsi.github.io/jiwer). + +## Installation + +You should be able to install this package using [poetry](https://python-poetry.org/docs/): + +``` +$ poetry add jiwer +``` + +Or, if you prefer old-fashioned pip and you're using Python >= `3.7`: + +```bash +$ pip install jiwer +``` + +## Usage + +The most simple use-case is computing the word error rate between two strings: + +```python +from jiwer import wer + +reference = "hello world" +hypothesis = "hello duck" + +error = wer(reference, hypothesis) +``` + +## Licence + +The jiwer package is released under the `Apache License, Version 2.0` licence by [8x8](https://www.8x8.com/). + +For further information, see [`LICENCE`](./LICENSE). + +## Reference + +_For a comparison between WER, MER and WIL, see: \ +Morris, Andrew & Maier, Viktoria & Green, Phil. (2004). [From WER and RIL to MER and WIL: improved evaluation measures for connected speech recognition.](https://www.researchgate.net/publication/221478089_From_WER_and_RIL_to_MER_and_WIL_improved_evaluation_measures_for_connected_speech_recognition)_ + + +%package -n python3-jiwer +Summary: Evaluate your speech-to-text system with similarity measures such as word error rate (WER) +Provides: python-jiwer +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-jiwer +# JiWER + +JiWER is a simple and fast python package to evaluate an automatic speech recognition system. +It supports the following measures: + +1. word error rate (WER) +2. match error rate (MER) +3. word information lost (WIL) +4. word information preserved (WIP) +5. character error rate (CER) + +These measures are computed with the use of the minimum-edit distance between one or more reference and hypothesis sentences. +The minimum-edit distance is calculated using [RapidFuzz](https://github.com/maxbachmann/RapidFuzz), which uses C++ under the hood, and is therefore faster than a pure python implementation. + +## Documentation + +For further info, see the documentation at [jitsi.github.io/jiwer](https://jitsi.github.io/jiwer). + +## Installation + +You should be able to install this package using [poetry](https://python-poetry.org/docs/): + +``` +$ poetry add jiwer +``` + +Or, if you prefer old-fashioned pip and you're using Python >= `3.7`: + +```bash +$ pip install jiwer +``` + +## Usage + +The most simple use-case is computing the word error rate between two strings: + +```python +from jiwer import wer + +reference = "hello world" +hypothesis = "hello duck" + +error = wer(reference, hypothesis) +``` + +## Licence + +The jiwer package is released under the `Apache License, Version 2.0` licence by [8x8](https://www.8x8.com/). + +For further information, see [`LICENCE`](./LICENSE). + +## Reference + +_For a comparison between WER, MER and WIL, see: \ +Morris, Andrew & Maier, Viktoria & Green, Phil. (2004). [From WER and RIL to MER and WIL: improved evaluation measures for connected speech recognition.](https://www.researchgate.net/publication/221478089_From_WER_and_RIL_to_MER_and_WIL_improved_evaluation_measures_for_connected_speech_recognition)_ + + +%package help +Summary: Development documents and examples for jiwer +Provides: python3-jiwer-doc +%description help +# JiWER + +JiWER is a simple and fast python package to evaluate an automatic speech recognition system. +It supports the following measures: + +1. word error rate (WER) +2. match error rate (MER) +3. word information lost (WIL) +4. word information preserved (WIP) +5. character error rate (CER) + +These measures are computed with the use of the minimum-edit distance between one or more reference and hypothesis sentences. +The minimum-edit distance is calculated using [RapidFuzz](https://github.com/maxbachmann/RapidFuzz), which uses C++ under the hood, and is therefore faster than a pure python implementation. + +## Documentation + +For further info, see the documentation at [jitsi.github.io/jiwer](https://jitsi.github.io/jiwer). + +## Installation + +You should be able to install this package using [poetry](https://python-poetry.org/docs/): + +``` +$ poetry add jiwer +``` + +Or, if you prefer old-fashioned pip and you're using Python >= `3.7`: + +```bash +$ pip install jiwer +``` + +## Usage + +The most simple use-case is computing the word error rate between two strings: + +```python +from jiwer import wer + +reference = "hello world" +hypothesis = "hello duck" + +error = wer(reference, hypothesis) +``` + +## Licence + +The jiwer package is released under the `Apache License, Version 2.0` licence by [8x8](https://www.8x8.com/). + +For further information, see [`LICENCE`](./LICENSE). + +## Reference + +_For a comparison between WER, MER and WIL, see: \ +Morris, Andrew & Maier, Viktoria & Green, Phil. (2004). [From WER and RIL to MER and WIL: improved evaluation measures for connected speech recognition.](https://www.researchgate.net/publication/221478089_From_WER_and_RIL_to_MER_and_WIL_improved_evaluation_measures_for_connected_speech_recognition)_ + + +%prep +%autosetup -n jiwer-3.0.1 + +%build +%py3_build + +%install +%py3_install +install -d -m755 %{buildroot}/%{_pkgdocdir} +if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi +if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi +if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi +if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi +pushd %{buildroot} +if [ -d usr/lib ]; then + find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/lib64 ]; then + find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/bin ]; then + find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst +fi +if [ -d usr/sbin ]; then + find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst +fi +touch doclist.lst +if [ -d usr/share/man ]; then + find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst +fi +popd +mv %{buildroot}/filelist.lst . +mv %{buildroot}/doclist.lst . + +%files -n python3-jiwer -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Tue Apr 11 2023 Python_Bot <Python_Bot@openeuler.org> - 3.0.1-1 +- Package Spec generated @@ -0,0 +1 @@ +4ac024b8463f74952a9797e2cd5814b4 jiwer-3.0.1.tar.gz |