Metadata-Version: 2.1
Name: pylabeador
Version: 0.2.0
Summary: Automatic syllabification for Spanish words
Home-page: https://github.com/jdevera/pylabeador
Author: Jacobo de Vera
Author-email: devel@jacobodevera.com
License: GPL-3.0-or-later
Description: # Pylabeador: Automatic Syllabification of Spanish Words
        
        ```python
        >>> import pylabeador
        >>> pylabeador.syllabify("silabear")
        ['si', 'la', 'be', 'ar']
        ```
        
        # Accuracy
        
        Automatic syllabification without additional lexical or and semantic *knowledge* of the words can only go so far.  This syllabifier does not have such knowledge. Because of this, words such as *transatlántico*, whose correct hyphenation is *trans-a-tlán-ti-co* or even *trans-at-lán-ti-co*, end up being divided here into *tran-sa-tlán-ti-co*.  To hyphenate this correctly, it is necessary to know that the word without the prefix exists in Spanish with similar semantics to the one of the original word. This is better and further explained in this paper: [Automatic syllabification for Spanish using lemmatization and derivation to solve the prefix’s prominence issue](http://dx.doi.org/10.1016/j.eswa.2013.06.056)
        
        # Inspiration / Original source
        
        This work is inspired by the excellent online tool [Silabeador TIP](https://tulengua.es/syllables/). This tool considers the semantics of the words and correctly separates syllables in the presence of prefixes. They also provide a C++ library that performs the naive syllable separation that *pylabeador* does. In fact, *pyleabeador* started as a Python port of that library.
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Text Processing
Classifier: Topic :: Text Processing :: Linguistic
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Natural Language :: Spanish
Description-Content-Type: text/markdown
