Probabilistic generation of weather forecast texts

Research output: Chapter in Book/Conference proceeding with ISSN or ISBNConference contribution with ISSN or ISBN

Abstract

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.
Original languageEnglish
Title of host publicationHuman Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Place of PublicationStroudsburg, PA, USA
PublisherAssociation for Computational Linguistics
Pages164-171
Number of pages8
Publication statusPublished - 1 Jan 2007
EventHuman Language Technology Conference of the North American Chapter of the Association of Computational Linguistics - Rochester, New York, USA
Duration: 1 Jan 2007 → …

Conference

ConferenceHuman Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Period1/01/07 → …

Bibliographical note

Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License . Permission is granted to make copies for the purposes of teaching and research.

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