Sashank Santhanam author Samira Shaikh author 2020-jul text Association for Computational Linguistics Seattle, USA conference publication Evaluation of output from natural language generation (NLG) systems is typically conducted via crowdsourced human judgments. To understand the impact of how experiment design might affect the quality and consistency of such human judgments, we designed a between-subjects study with four experimental conditions. Through our systematic study with 40 crowdsourced workers in each task, we find that using continuous scales achieves more consistent ratings than Likert scale or ranking-based experiment design. Additionally, we find that factors such as no prior experience of participating in similar studies of rating dialogue system output santhanam-shaikh-2020-understanding 2020-jul 124 127