Dynamic Human Evaluation for Relative Model Comparisons
Autor: | Thórhildur Thorleiksdóttir, Cedric Renggli, Nora Hollenstein, Ce Zhang |
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Přispěvatelé: | Calzolari, Nicoletta, Béchet, Frédéric, Blache, Philippe, Choukri, Khalid, Cieri, Christopher, Declerck, Thierry, Goggi, Sara, Isahara, Hitoshi, Maegaard, Bente, Mariani, Joseph, Mazo, Hélène, Odijk, Jan, Piperidis, Stelios |
Jazyk: | angličtina |
Rok vydání: | 2022 |
Předmět: | |
Zdroj: | Thorleiksdóttir, T, Renggli, C, Hollenstein, N & Zhang, C 2022, Dynamic Human Evaluation for Relative Model Comparisons . in Proceedings of the Thirteenth Language Resources and Evaluation Conference . European Language Resources Association, Marseille, France, pp. 5946-5955 . < https://aclanthology.org/2022.lrec-1.639 > Proceedings of the Thirteenth Language Resources and Evaluation Conference University of Copenhagen |
Popis: | Collecting human judgements is currently the most reliable evaluation method for natural language generation systems. Automatic metrics have reported flaws when applied to measure quality aspects of generated text and have been shown to correlate poorly with human judgements. However, human evaluation is time and cost-intensive, and we lack consensus on designing and conducting human evaluation experiments. Thus there is a need for streamlined approaches for efficient collection of human judgements when evaluating natural language generation systems. Therefore, we present a dynamic approach to measure the required number of human annotations when evaluating generated outputs in relative comparison settings. We propose an agent-based framework of human evaluation to assess multiple labelling strategies and methods to decide the better model in a simulation and a crowdsourcing case study. The main results indicate that a decision about the superior model can be made with high probability across different labelling strategies, where assigning a single random worker per task requires the least overall labelling effort and thus the least cost. Proceedings of the Thirteenth Language Resources and Evaluation Conference ISBN:979-10-95546-72-6 |
Databáze: | OpenAIRE |
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