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Human evaluation is often considered to be the gold standard method ofevaluating a Natural Language Generation system. However, whilst its importanceis accepted by the community at large, the quality of its execution is oftenbrought into question. In this position paper, we argue that the generation ofmore esoteric forms of language - humour, irony and sarcasm - constitutes asubdomain where the characteristics of selected evaluator panels are of utmostimportance, and every effort should be made to report demographiccharacteristics wherever possible, in the interest of transparency andreplicability. We support these claims with an overview of each language formand an analysis of examples in terms of how their interpretation is affected bydifferent participant variables. We additionally perform a critical survey ofrecent works in NLG to assess how well evaluation procedures are reported inthis subdomain, and note a severe lack of open reporting of evaluatordemographic information, and a significant reliance on crowdsourcing platformsfor recruitment.

The Iron(ic) Melting Pot: Reviewing Human Evaluation in Humour, Irony and Sarcasm Generation