%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 - 1.0.11-1 - Package Spec generated