We ask subjects whether they perceive as human-produced a bunch of texts, some of which are actually human-written, while others are automatically generated.
Figurative language generation is the task of reformulating a given text in the desired figure of speech while still being faithful to the original context.
Although text style transfer has witnessed rapid development in recent years, there is as yet no established standard for evaluation, which is performed using several automatic metrics, lacking the possibility of always resorting to human judgement.
Style transfer aims to rewrite a source text in a different target style while preserving its content.
An ongoing debate in the NLG community concerns the best way to evaluate systems, with human evaluation often being considered the most reliable method, compared to corpus-based metrics.