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diff --git a/python-g2p-en.spec b/python-g2p-en.spec new file mode 100644 index 0000000..ad6c0ab --- /dev/null +++ b/python-g2p-en.spec @@ -0,0 +1,136 @@ +%global _empty_manifest_terminate_build 0 +Name: python-g2p-en +Version: 2.1.0 +Release: 1 +Summary: A Simple Python Module for English Grapheme To Phoneme Conversion +License: Apache Software License +URL: https://github.com/Kyubyong/g2p +Source0: https://mirrors.nju.edu.cn/pypi/web/packages/5f/22/2c7acbe6164ed6cfd4301e9ad2dbde69c68d22268a0f9b5b0ee6052ed3ab/g2p_en-2.1.0.tar.gz +BuildArch: noarch + +Requires: python3-numpy +Requires: python3-nltk +Requires: python3-inflect +Requires: python3-distance + +%description +[Update] * We removed TensorFlow from the dependencies. After all, it changes its APIs quite often, and we don't expect you to have a GPU. Instead, NumPy is used for inference. +This module is designed to convert English graphemes (spelling) to +phonemes (pronunciation). It is considered essential in several tasks +such as speech synthesis. Unlike many languages like Spanish or German +where pronunciation of a word can be inferred from its spelling, English +words are often far from people's expectations. Therefore, it will be +the best idea to consult a dictionary if we want to know the +pronunciation of some word. However, there are at least two tentative +issues in this approach. First, you can't disambiguate the pronunciation +of homographs, words which have multiple pronunciations. (See ``a`` +below.) Second, you can't check if the word is not in the dictionary. +(See ``b`` below.) +- + \a. I refuse to collect the refuse around here. (rɪ\|fju:z as verb vs. \|refju:s as noun) +- + \b. I am an activationist. (activationist: newly coined word which means ``n. A person who designs and implements programs of treatment or therapy that use recreation and activities to help people whose functional abilities are affected by illness or disability.`` from `WORD SPY <https://wordspy.com/index.php?word=activationist>`__ +For the first homograph issue, fortunately many homographs can be +disambiguated using their part-of-speech, if not all. When it comes to +the words not in the dictionary, however, we should make our best guess +using our knowledge. In this project, we employ a deep learning seq2seq +framework based on TensorFlow. + +%package -n python3-g2p-en +Summary: A Simple Python Module for English Grapheme To Phoneme Conversion +Provides: python-g2p-en +BuildRequires: python3-devel +BuildRequires: python3-setuptools +BuildRequires: python3-pip +%description -n python3-g2p-en +[Update] * We removed TensorFlow from the dependencies. After all, it changes its APIs quite often, and we don't expect you to have a GPU. Instead, NumPy is used for inference. +This module is designed to convert English graphemes (spelling) to +phonemes (pronunciation). It is considered essential in several tasks +such as speech synthesis. Unlike many languages like Spanish or German +where pronunciation of a word can be inferred from its spelling, English +words are often far from people's expectations. Therefore, it will be +the best idea to consult a dictionary if we want to know the +pronunciation of some word. However, there are at least two tentative +issues in this approach. First, you can't disambiguate the pronunciation +of homographs, words which have multiple pronunciations. (See ``a`` +below.) Second, you can't check if the word is not in the dictionary. +(See ``b`` below.) +- + \a. I refuse to collect the refuse around here. (rɪ\|fju:z as verb vs. \|refju:s as noun) +- + \b. I am an activationist. (activationist: newly coined word which means ``n. A person who designs and implements programs of treatment or therapy that use recreation and activities to help people whose functional abilities are affected by illness or disability.`` from `WORD SPY <https://wordspy.com/index.php?word=activationist>`__ +For the first homograph issue, fortunately many homographs can be +disambiguated using their part-of-speech, if not all. When it comes to +the words not in the dictionary, however, we should make our best guess +using our knowledge. In this project, we employ a deep learning seq2seq +framework based on TensorFlow. + +%package help +Summary: Development documents and examples for g2p-en +Provides: python3-g2p-en-doc +%description help +[Update] * We removed TensorFlow from the dependencies. After all, it changes its APIs quite often, and we don't expect you to have a GPU. Instead, NumPy is used for inference. +This module is designed to convert English graphemes (spelling) to +phonemes (pronunciation). It is considered essential in several tasks +such as speech synthesis. Unlike many languages like Spanish or German +where pronunciation of a word can be inferred from its spelling, English +words are often far from people's expectations. Therefore, it will be +the best idea to consult a dictionary if we want to know the +pronunciation of some word. However, there are at least two tentative +issues in this approach. First, you can't disambiguate the pronunciation +of homographs, words which have multiple pronunciations. (See ``a`` +below.) Second, you can't check if the word is not in the dictionary. +(See ``b`` below.) +- + \a. I refuse to collect the refuse around here. (rɪ\|fju:z as verb vs. \|refju:s as noun) +- + \b. I am an activationist. (activationist: newly coined word which means ``n. A person who designs and implements programs of treatment or therapy that use recreation and activities to help people whose functional abilities are affected by illness or disability.`` from `WORD SPY <https://wordspy.com/index.php?word=activationist>`__ +For the first homograph issue, fortunately many homographs can be +disambiguated using their part-of-speech, if not all. When it comes to +the words not in the dictionary, however, we should make our best guess +using our knowledge. In this project, we employ a deep learning seq2seq +framework based on TensorFlow. + +%prep +%autosetup -n g2p-en-2.1.0 + +%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-g2p-en -f filelist.lst +%dir %{python3_sitelib}/* + +%files help -f doclist.lst +%{_docdir}/* + +%changelog +* Tue Apr 11 2023 Python_Bot <Python_Bot@openeuler.org> - 2.1.0-1 +- Package Spec generated |