Judge the Judges: A Large-Scale Evaluation Study of Neural Language Models for Online Review Generation

Cristina Garbacea, Samuel Carton, Shiyan Yan, Qiaozhu Mei


Abstract
We conduct a large-scale, systematic study to evaluate the existing evaluation methods for natural language generation in the context of generating online product reviews. We compare human-based evaluators with a variety of automated evaluation procedures, including discriminative evaluators that measure how well machine-generated text can be distinguished from human-written text, as well as word overlap metrics that assess how similar the generated text compares to human-written references. We determine to what extent these different evaluators agree on the ranking of a dozen of state-of-the-art generators for online product reviews. We find that human evaluators do not correlate well with discriminative evaluators, leaving a bigger question of whether adversarial accuracy is the correct objective for natural language generation. In general, distinguishing machine-generated text is challenging even for human evaluators, and human decisions correlate better with lexical overlaps. We find lexical diversity an intriguing metric that is indicative of the assessments of different evaluators. A post-experiment survey of participants provides insights into how to evaluate and improve the quality of natural language generation systems.
Anthology ID:
D19-1409
Volume:
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
Month:
November
Year:
2019
Address:
Hong Kong, China
Venues:
EMNLP | IJCNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
3968–3981
Language:
URL:
https://aclanthology.org/D19-1409
DOI:
10.18653/v1/D19-1409
Bibkey:
Cite (ACL):
Cristina Garbacea, Samuel Carton, Shiyan Yan, and Qiaozhu Mei. 2019. Judge the Judges: A Large-Scale Evaluation Study of Neural Language Models for Online Review Generation. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 3968–3981, Hong Kong, China. Association for Computational Linguistics.
Cite (Informal):
Judge the Judges: A Large-Scale Evaluation Study of Neural Language Models for Online Review Generation (Garbacea et al., EMNLP 2019)
Copy Citation:
PDF:
https://aclanthology.org/D19-1409.pdf
Attachment:
 D19-1409.Attachment.pdf
Code
 Crista23/JudgeTheJudges