"Let Everything Turn Well in Your Wife": Generation of Adult Humor Using Lexical Constraints
Valitutti, Alessandro and Toivonen, Hannu and Doucet, Antoine and Toivanen, Jukka M.

Article Structure

Abstract

We propose a method for automated generation of adult humor by lexical replacement and present empirical evaluation results of the obtained humor.

Introduction

Incongruity and taboo meanings are typical ingredients of humor.

Background

Humor, Incongruity and Tabooness A set of theories known as incongruity theory is probably the most influential approach to the study of humor and laughter.

Lexical Constraints for Humorous Word Substitution

The procedure gets as input a segment of English text (e.g.

Evaluation

We evaluated the method empirically using CrowdFlower5, a crowdsourcing service.

Conclusions

We have proposed a new approach for the study of computational humor generation by lexical replacement.

Topics

UA

Appears in 4 sentences as: UA (5)
In "Let Everything Turn Well in Your Wife": Generation of Adult Humor Using Lexical Constraints
  1. For the analysis of the results, we then measured the effectiveness of the constraints using two derived variables: the Collective F unniness (CF) of a message is its mean funniness, while its Upper Agreement ( UA (t)) is the fraction of funniness scores greater than or equal to a given threshold 75.
    Page 4, “Evaluation”
  2. To rank the generated messages, we take the product of Collective Funniness and Upper Agreement UA (3) and call it the overall Humor Eflectiveness (HE).
    Page 4, “Evaluation”
  3. The Upper Agreement UA (4) increases from 0.18 to 0.36 and to 0.43, respectively.
    Page 4, “Evaluation”
  4. We analyzed the distributions of Collective Funniness values of messages, as well as the distributions of their Upper Agreements (for all values from UA(2) to UA (5)) under the three conditions.
    Page 4, “Evaluation”

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n-grams

Appears in 3 sentences as: n-grams (4)
In "Let Everything Turn Well in Your Wife": Generation of Adult Humor Using Lexical Constraints
  1. Implementation Local coherence is implemented using n-grams .
    Page 3, “Lexical Constraints for Humorous Word Substitution”
  2. To estimate the level of expectation triggered by a left-context, we rely on a vast collection of n-grams, the 2012 Google Books n-grams collection4 (Michel et al., 2011) and compute the cohesion of each n-gram, by comparing their expected frequency (assuming word inde-pence), to their observed number of occurrences.
    Page 3, “Lexical Constraints for Humorous Word Substitution”
  3. In particular, we plan to extend the use of n-grams to larger contexts and consider more fine-grained tuning of other constraints, too.
    Page 5, “Conclusions”

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statistical significance

Appears in 3 sentences as: statistical significance (2) statistically significantly (1)
In "Let Everything Turn Well in Your Wife": Generation of Adult Humor Using Lexical Constraints
  1. The evaluations indicate statistical significance , but the test settings are relatively specific.
    Page 2, “Background”
  2. According to the one-sided Wilcoxon rank-sum test, both Collective Funniness and all Upper Agreements increase from FORM to FORM+TABOO and from FORM+TABOO to FORM+TABOO+CONT statistically significantly (in all cases p < .002).
    Page 4, “Evaluation”
  3. The statistical significance is particularly high, even though there were several limitations in the experimental setting.
    Page 4, “Conclusions”

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