Quality Assessment Of Automatic Paraphrasing Tool For English: An Analysis At Lexical Level

Abstract

Automated paraphrasing is considered an important and emerging educational phenomenon that has a key role in academia. Paraphrasing tools facilitate students as well as professionals’ work. However, there is a need to assess and evaluate the quality of automated paraphrasing by such paraphrasing tools. This study aims at evaluating the quality of automated paraphrasing carried out by one of such tools, that is, QuillBot, by exploring the lexical relatedness and differences in the original and the paraphrased text. Hence, the limitations of automated paraphrasing tools are highlighted. In this regard, QuillBot is used for paraphrasing as it is considered a standard paraphrasing tool by many. Automated paraphrasing of literary and non-literary text carried out by QuillBot is used as data. AntConc, a corpus tool, is used for exploring the lexical features of the data. In addition, word relatedness is also computed from HSO measure through the WS4J demo, an online WordNet ontological tool. Differences were found at the lexical level between the original and paraphrased text. Automated paraphrasing carried out by QuillBot of the non-literary text is more aligned with the original text than that of the literary text. In the lexical category, mostly content words were substituted with synonymous words. The morphological structure of words was also modified. At times, these alterations would obscure the original meaning, while on other occasions, they would enhance and refine it.Therefore, automated paraphrasing should not be taken for granted instead, it should be subject to manual review and revisions. In addition to automated paraphrasing of literary text carried out by such tools, it should be rechecked and updated manually while standard tools, like QuillBot, could be relied upon for paraphrasing of non-literary text.