Paper: Probabilistic Generation of Weather Forecast Texts

ACL ID N07-1021
Title Probabilistic Generation of Weather Forecast Texts
Venue Human Language Technologies
Session Main Conference
Year 2007
Authors
  • Anja Belz (University of Brighton, Brighton UK)

This paper reports experiments in which pCRU — a generation framework that combines probabilistic generation methodology with a comprehensive model of the generation space — is used to semi-automatically create sev- eral versions of a weather forecast text generator. The generators are evaluated in terms of output quality, development time and computational efficiency against (i) human forecasters, (ii) a traditional handcrafted pipelined NLG system, and (iii) a HALOGEN-style statistical genera- tor. The most striking result is that despite acquiring all decision-making abilities automatically, the best pCRU generators receive higher scores from human judges than forecasts written by experts.