Generating punning riddles from examples

• Main Authors: Hong, Bryan Anthony, Ong, Ethel C.
• Format: text
• Published: Animo Repository 2008
• Subjects: Natural language generation (Computer science); Puns and punning; Computer Sciences
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/4431
• Institution: De La Salle University

Text generation systems, such as pun generators, depend on manually created templates which require a lot of effort to build. This paper presents T-Peg, a system that utilizes semantic and phonetic knowledge sources to automatically capture the wordplay patterns of human-made jokes from training examples. The knowledge learned are stored as templates which, combined with a keyword input from the user, can then be used to generate punning riddles. Manual evaluation by a linguist on the completeness of the learned templates gave the system a score of 4.0 out of 5. User feedback gave the computer-generated puns an average score of 2.13 out of 5, as compared to their human-made counterparts which received an average score of 2.70, demonstrating that computers can be trained to be as humorous as humans. © 2008 IEEE.