Árbore:
1a80a96741
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12.0
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bedlam
bedlam-name-fixes
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user/anddt/network/umurmur
user/anddt/network/yt-dlp
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user/anddt/office/gnumeric
user/anddt/office/sigil
user/anddt/system/FontAwesome
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user/anddt/system/fakeroot
user/anddt/system/hplip-plugin
user/anddt/system/postgresql
user/anddt/system/testdisk
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user/dslackw/updates
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willysr
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Heinz Wiesinger
63daf9f79a
All: Support $PRINT_PACKAGE_NAME env var
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%!s(int64=3) %!d(string=hai) anos | |
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| .. | ||
| README | 0a451da746 perl/perl-Lingua-EN-Syllable: Added (short description of app). | %!s(int64=6) %!d(string=hai) anos |
| perl-Lingua-EN-Syllable.SlackBuild | 63daf9f79a All: Support $PRINT_PACKAGE_NAME env var | %!s(int64=3) %!d(string=hai) anos |
| perl-Lingua-EN-Syllable.info | 0a451da746 perl/perl-Lingua-EN-Syllable: Added (short description of app). | %!s(int64=6) %!d(string=hai) anos |
| slack-desc | 0a451da746 perl/perl-Lingua-EN-Syllable: Added (short description of app). | %!s(int64=6) %!d(string=hai) anos |
README
perl-Linuga-EN-Syllable
Lingua::EN::Syllable::syllable() estimates the number of syllables in
the word passed to it.
Note that it isn't entirely accurate... it fails (by one syllable) for
about 10-15% of my /usr/dict/words. The only way to get a 100% accurate
count is to do a dictionary lookup, so this is a small and fast
alternative where more-or-less accurate results will suffice, such as
estimating the reading level of a document.
I welcome pointers to more accurate algorithms, since this one is
pretty quick-and-dirty. This was designed for English (well, American
at least) words, but sometimes guesses well for other languages.
Lingua::EN::Syllable::syllable() estimates the number of syllables in
the word passed to it.
Note that it isn't entirely accurate... it fails (by one syllable) for
about 10-15% of my /usr/dict/words. The only way to get a 100% accurate
count is to do a dictionary lookup, so this is a small and fast
alternative where more-or-less accurate results will suffice, such as
estimating the reading level of a document.
I welcome pointers to more accurate algorithms, since this one is
pretty quick-and-dirty. This was designed for English (well, American
at least) words, but sometimes guesses well for other languages.