Our mission is simple: Develop text analysis tools for low-resource languages.
SyllabiPy was created by Alex Estes and Christopher Hench at the University of California, Berkeley in 2015. Alex and Christopher are graduate students in the German Department interested in linguistic forces operating in literature, and the tools of the Digital Humanities.
SyllabiPy is a Python library, which syllabify words and tag syllables for qualities. It was originally written for use with Middle High German text analysis. The same algorithm can be applied to many different languages, but must be customized for each. The SyllabiPy project aims to expand support primarily for historical languages, as modern languages are often covered by dictionary look-up techniques. While the general principles of SyllabiPy are simple, accomplishing this in Python opens up a whole world of text analysis tools. As it stands the code yields syllables along with tags for light, heavy, open, and closed syllables.
- Expand syllabification support for other historical languages (Old High German, Gothic, Old Norse, Old French, Old Occitan, Old English).
- Integrate tags for syllable quality (heavy, light, open, closed).
- Explore implications for text analysis and the humanities.
SyllabiPy is indebted to the Digital Humanities at Berkeley initiative, both for financial and technical support.