Twenty Years of Confusion in Human Evaluation: NLG Needs Evaluation Sheets and Standardised Definitions

David M. Howcroft, Anya Belz, Miruna-Adriana Clinciu, Dimitra Gkatzia, Sadid A. Hasan, Saad Mahamood, Simon Mille, Emiel van Miltenburg, Sashank Santhanam, Verena Rieser

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Abstract

Human assessment remains the most trusted form of evaluation in NLG, but highly diverse approaches and a proliferation of different quality criteria used by researchers make it difficult to compare results and draw conclusions across papers, with adverse implications for meta-evaluation and reproducibility. In this paper, we present (i) our dataset of 165 NLG papers with human evaluations, (ii) the annotation scheme we developed to label the papers for different aspects of evaluations, (iii) quantitative analyses of the annotations, and (iv) a set of recommendations for improving standards in evaluation reporting. We use the annotations as a basis for examining information included in evaluation reports, and levels of consistency in approaches, experimental design and terminology, focusing in particular on the 200+ different terms that have been used for evaluated aspects of quality. We conclude that due to a pervasive lack of clarity in reports and extreme diversity in approaches, human evaluation in NLG presents as extremely confused in 2020, and that the field is in urgent need of standard methods and terminology.
Original languageEnglish
Title of host publicationProceedings of the 13th International Conference on Natural Language Generation
Place of PublicationDublin, Ireland
PublisherAssociation for Computational Linguistics
Pages169-182
Number of pages14
Publication statusPublished - 1 Dec 2020
EventInternational Conference on Natural Language Generation - online, Dublin , Ireland
Duration: 15 Dec 202018 Dec 2020
Conference number: 13
https://www.inlg2020.org/

Conference

ConferenceInternational Conference on Natural Language Generation
Abbreviated titleINLG 2020
CountryIreland
CityDublin
Period15/12/2018/12/20
Internet address

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