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%global _empty_manifest_terminate_build 0
Name: python-AMFM-decompy
Version: 1.0.11
Release: 1
Summary: Package containing the tools necessary for decomposing a speech signal into its modulated components, aka AM-FM decomposition.
License: LICENSE.txt
URL: https://github.com/bjbschmitt/AMFM_decompy/
Source0: https://mirrors.aliyun.com/pypi/web/packages/e7/ea/9364ece82c511c85131e24012dcf37d2aca876db7ea18799e8969fc5e8b6/AMFM_decompy-1.0.11.tar.gz
BuildArch: noarch
%description
version 1.0.11
This python package provides the tools necessary for decomposing the voiced part of a speech signal into its modulated components, aka AM-FM decomposition. This designation is used due the fact that, in this method, the signal is modeled as a sum of amplitude- and frequency-modulated components.
The goal is to overcome the drawbacks from Fourier-alike techniques, e.g. SFFT, wavelets, etc, which are limited in the time-frequency analysis by the so-called Heisenberg-Gabor inequality.
The algorithms here implemented are the QHM (Quasi-Harmonic Model), and its upgrades, aQHM (adaptive Quasi-Harmonic Model) and eaQHM (extended adaptive Quasi-Harmonic Model). Their formulation can be found at references [2-4].
Since that the tools mentioned above require a fundamental frequency reference, the package also includes the pitch tracker YAAPT (Yet Another Algorithm for Pitch Tracking) [1], which is extremely robust for both high quality and telephone speech.
The study of AM-FM decomposition algorithms was the theme from my Master Thesis. The original YAAPT program in MATLAB is provided for free by its authors, while the QHM algorithms I implemented by myself also in MATLAB. I'm porting them now to python because:
* the python language is easier to share, read and understand, making it a better way to distribute the codes;
* is more resourceful than MATLAB (has different data structures, scripting options, etc), which will be useful for me in future studies;
* the computational performance from its numeric and scientific packages (numpy and scipy) is equivalent to MATLAB;
* python is free-to-use, while MATLAB is a proprietary software;
%package -n python3-AMFM-decompy
Summary: Package containing the tools necessary for decomposing a speech signal into its modulated components, aka AM-FM decomposition.
Provides: python-AMFM-decompy
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-AMFM-decompy
version 1.0.11
This python package provides the tools necessary for decomposing the voiced part of a speech signal into its modulated components, aka AM-FM decomposition. This designation is used due the fact that, in this method, the signal is modeled as a sum of amplitude- and frequency-modulated components.
The goal is to overcome the drawbacks from Fourier-alike techniques, e.g. SFFT, wavelets, etc, which are limited in the time-frequency analysis by the so-called Heisenberg-Gabor inequality.
The algorithms here implemented are the QHM (Quasi-Harmonic Model), and its upgrades, aQHM (adaptive Quasi-Harmonic Model) and eaQHM (extended adaptive Quasi-Harmonic Model). Their formulation can be found at references [2-4].
Since that the tools mentioned above require a fundamental frequency reference, the package also includes the pitch tracker YAAPT (Yet Another Algorithm for Pitch Tracking) [1], which is extremely robust for both high quality and telephone speech.
The study of AM-FM decomposition algorithms was the theme from my Master Thesis. The original YAAPT program in MATLAB is provided for free by its authors, while the QHM algorithms I implemented by myself also in MATLAB. I'm porting them now to python because:
* the python language is easier to share, read and understand, making it a better way to distribute the codes;
* is more resourceful than MATLAB (has different data structures, scripting options, etc), which will be useful for me in future studies;
* the computational performance from its numeric and scientific packages (numpy and scipy) is equivalent to MATLAB;
* python is free-to-use, while MATLAB is a proprietary software;
%package help
Summary: Development documents and examples for AMFM-decompy
Provides: python3-AMFM-decompy-doc
%description help
version 1.0.11
This python package provides the tools necessary for decomposing the voiced part of a speech signal into its modulated components, aka AM-FM decomposition. This designation is used due the fact that, in this method, the signal is modeled as a sum of amplitude- and frequency-modulated components.
The goal is to overcome the drawbacks from Fourier-alike techniques, e.g. SFFT, wavelets, etc, which are limited in the time-frequency analysis by the so-called Heisenberg-Gabor inequality.
The algorithms here implemented are the QHM (Quasi-Harmonic Model), and its upgrades, aQHM (adaptive Quasi-Harmonic Model) and eaQHM (extended adaptive Quasi-Harmonic Model). Their formulation can be found at references [2-4].
Since that the tools mentioned above require a fundamental frequency reference, the package also includes the pitch tracker YAAPT (Yet Another Algorithm for Pitch Tracking) [1], which is extremely robust for both high quality and telephone speech.
The study of AM-FM decomposition algorithms was the theme from my Master Thesis. The original YAAPT program in MATLAB is provided for free by its authors, while the QHM algorithms I implemented by myself also in MATLAB. I'm porting them now to python because:
* the python language is easier to share, read and understand, making it a better way to distribute the codes;
* is more resourceful than MATLAB (has different data structures, scripting options, etc), which will be useful for me in future studies;
* the computational performance from its numeric and scientific packages (numpy and scipy) is equivalent to MATLAB;
* python is free-to-use, while MATLAB is a proprietary software;
%prep
%autosetup -n AMFM_decompy-1.0.11
%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-AMFM-decompy -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Thu Jun 08 2023 Python_Bot <Python_Bot@openeuler.org> - 1.0.11-1
- Package Spec generated
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