automatic import of python-jiwer

3 files changed, 241 insertions, 0 deletions

diff --git a/.gitignore b/.gitignore
index e69de29..447dbaf 100644
--- a/.gitignore
+++ b/.gitignore
@@ -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
diff --git a/sources b/sources
new file mode 100644
index 0000000..4eb3357
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+4ac024b8463f74952a9797e2cd5814b4  jiwer-3.0.1.tar.gz