Automatic Target Recovery for Hindi-English Code Mixed Puns

TL;DR

This paper develops a system to identify and recover the targets of Hindi-English code-mixed puns, enhancing computational understanding of humor in multilingual social media content.

Contribution

It introduces a classification of code-mixed puns and proposes a four-step algorithm utilizing language models and phonetic features for target recovery.

Findings

Successfully recovers pun targets for 67% of cases

Classifies puns into intra-sentential and intra-word categories

Demonstrates effectiveness on social media advertisements

Abstract

In order for our computer systems to be more human-like, with a higher emotional quotient, they need to be able to process and understand intrinsic human language phenomena like humour. In this paper, we consider a subtype of humour - puns, which are a common type of wordplay-based jokes. In particular, we consider code-mixed puns which have become increasingly mainstream on social media, in informal conversations and advertisements and aim to build a system which can automatically identify the pun location and recover the target of such puns. We first study and classify code-mixed puns into two categories namely intra-sentential and intra-word, and then propose a four-step algorithm to recover the pun targets for puns belonging to the intra-sentential category. Our algorithm uses language models, and phonetic similarity-based features to get the desired results. We test our approach on a small set of code-mixed punning advertisements, and observe that our system is successfully able to recover the targets for 67% of the puns.