Summary of the paper

Title Comparison of Pun Detection Methods Using Japanese Pun Corpus
Authors Motoki Yatsu and Kenji Araki
Abstract A sampling survey of typology and component ratio analysis in Japanese puns revealed that the type of Japanese pun that had the largest proportion was a pun type with two sound sequences, whose consonants are phonetically close to each other in the same sentence which includes the pun. Based on this finding, we constructed rules to detect pairs of phonetically similar sequences as features for a supervised machine learning classifier. Using these features in addition to Bag-of-Words features, an evaluation experiment confirmed the effectiveness of adding the rule-based features to the baseline.
Topics Phonetic Databases, Phonology, Language Modelling, Corpus (Creation, Annotation, Etc.)
Full paper Comparison of Pun Detection Methods Using Japanese Pun Corpus
Bibtex @InProceedings{YATSU18.587,
  author = {Motoki Yatsu and Kenji Araki},
  title = "{Comparison of Pun Detection Methods Using Japanese Pun Corpus}",
  booktitle = {Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)},
  year = {2018},
  month = {May 7-12, 2018},
  address = {Miyazaki, Japan},
  editor = {Nicoletta Calzolari (Conference chair) and Khalid Choukri and Christopher Cieri and Thierry Declerck and Sara Goggi and Koiti Hasida and Hitoshi Isahara and Bente Maegaard and Joseph Mariani and Hélène Mazo and Asuncion Moreno and Jan Odijk and Stelios Piperidis and Takenobu Tokunaga},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {979-10-95546-00-9},
  language = {english}
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