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Does It Capture STEL? A Modular, Similarity-based Linguistic Style Evaluation Framework

2021-09-10 12:03:19
Anna Wegmann, Dong Nguyen
arXiv_CL
     
Abstract

Style is an integral part of natural language. However, evaluation methods for style measures are rare, often task-specific and usually do not control for content. We propose the modular, fine-grained and content-controlled similarity-based STyle EvaLuation framework (STEL) to test the performance of any model that can compare two sentences on style. We illustrate STEL with two general dimensions of style (formal/informal and simple/complex) as well as two specific characteristics of style (contrac'tion and numb3r substitution). We find that BERT-based methods outperform simple versions of commonly used style measures like 3-grams, punctuation frequency and LIWC-based approaches. We invite the addition of further tasks and task instances to STEL and hope to facilitate the improvement of style-sensitive measures.

Abstract (translated)

URL

https://arxiv.org/abs/2109.04817

PDF

https://arxiv.org/pdf/2109.04817.pdf

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