Generating récit from sensor data: Evaluation of a task model for story planning and preliminary experiments with GPS data

Abstract

Automatic story generation is the subject of a growing research effort which has mainly focused on fictional stories. In this paper, we present some preliminary work to generate récits (stories) from sensors data acquired during a ski sortie. In this approach, the story planning is performed using a task model that represents domain knowledge and sequential constraints between ski activities. To test the validity of the task model, a small-scale user evaluation was performed to compare the human perception of récit plans from hand written or automatically generated récits. This evaluation showed no difference in story plan identification adding credence to the eligibility of the task model for representing story plan in NLG. To go a step further, a basic NLG system to generate narrative from activities extracted from GPS data is also reported.