Is Neural Language Model Perplexity Related to Readability?

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Abstract

This paper explores the relationship between Neural Language Model (NLM) perplexity and sentence readability. Starting from the evidence that NLMs implicitly acquire sophisticated linguistic knowledge from a huge amount of training data, our goal is to investigate whether perplexity is affected by linguistic features used to automatically assess sentence readability and if there is a correlation between the two metrics. Our findings suggest that this correlation is actually quite weak and the two metrics are affected by different linguistic phenomena.

Citation

@inproceedings{miaschi2020neural,
  title={Is Neural Language Model Perplexity Related to Readability?},
  author={Miaschi, Alessio and Alzetta, Chiara and Brunato, Dominique and Dell’Orletta, Felice and Venturi, Giulia},
  booktitle={Proceedings of the Seventh Italian Conference on Computational Linguistics (CLiC-it)},
  year={2020}
}