Difference between revisions of "Language Processing for Art"

Revision as of 08:13, 7 May 2009

Language Processing for Art: Reading, Writing, Listening, Speaking.

This course explores the relationship between text and image, interactivity, and the database/archive from the perspective of contemporary language processing techologies.

We will survey recent developments from the fields of natural language processing (NLP) and computational linguistics (CL) as well as relevant artistic upper-level course exploring natural language processing (NLP) and computational linguistics (CL) as applied to art. It explores questions of the relationship between text and image, interactivity, and the database/archive from the perspective of contemporary language processing technologies. This is an upper-level course, and requires previous programming experience.

Python Natural Language Tool Kit (http://nltk.org) Notes on the Index. Rosalind Krauss. Database Aesthetics. Lev Manovich.

Semantic Web. XML. metadata. automatic content extraction.

• Semantic measures:
  • Perl WN-SIMILARITY http://wn-similarity.sourceforge.net/
• machine reading
  • optical character recognition
• machine writing
  • text generation
• listening
  • speech recognition http://cmusphinx.sourceforge.net/sphinx4/
  • language recognition
  • automatic-phone systems
• talking
  • speech synthesis
  • O.S. built in speech synthesis
  • accessibility tools