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Jokingbird: Funny Headline Generation for News
In this study, we address the problem of generating funny headlines for news articles. Funny headlines are beneficial even for serious news stories – they attract and entertain the reader. Automatically generated funny headlines can serve as prompts for news editors. More generally, humor generation can be applied to other domains, e.g. conversational systems. Like previous approaches, our methods are based on lexical substitutions. We consider two techniques for generating substitute words: one based on BERT and another based on collocation strength and semantic distance. At the final stage, a humor classifier chooses the funniest variant from the generated pool. An in-house evaluation of 200 generated headlines showed that the BERT-based model produces the funniest and in most cases grammatically correct output.