Task demands and individual variation in referring expressions

Aiming to improve the human-likeness of natural language generation systems, this study investigates different sources of variation that might influence the production of referring expressions (REs), namely the effect of task demands and interintraindividual variation. We collected REs using a discrimination game and varied the instructions, telling speakers that they would get points for being fast, creative, clear, or no incentive would be mentioned. Our results show that taskdemands affected REs production (number of words, number of attributes), and we observe a considerable amount of variation among the length of REs produced by single speakers, as well as among the REs of different speakers referring to the same targets.