Papers by Anirudh Mittal
“So You Think You’re Funny?”: Rating the Humour Quotient in Standup Comedy (2021.emnlp-main)
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| Challenge: | Existing datasets for humour classification are limited due to the subjectivity of the content and the multiple interpretations of the data. |
| Approach: | They propose to annotate a multi-modal humour-annotated dataset using stand-up comedy clips and compute a humor quotient using the audience's laughter. |
| Outcome: | The proposed scoring mechanism is validated by comparing with manual scoring methods and achieves an accuracy of 0.813 in terms of QWK. |
AmbiPun: Generating Humorous Puns with Ambiguous Context (2022.naacl-main)
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| Challenge: | Existing methods for generating homographic puns are heavy-weighted due to the lack of training data. |
| Approach: | They propose a way to generate pun sentences that does not require training on existing puns. |
| Outcome: | The proposed method outperforms baseline models and state-of-the-art models by a large margin. |