Belz, Anja

English

This paper reports experiments in which pC RU — a generation framework that combines probabilistic generation methodology with a comprehensive model of the generation space — is used to semi-automatically create several 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 generator. The most striking result is that despite acquiring all decision-making abilities automatically, the best pC RU generators receive higher scores from human judges than forecasts written by experts

University of Brighton Research Portal

Probabilistic generation of weather forecast texts

https://cris.brighton.ac.uk/ws/files/183998/belz-hltnaacl07.pdf

Probabilistic generation of weather forecast texts

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University of Brighton Research Portal