To computationally model a meaning-preserved variance of text across styles, many recent works have developed systems that transfer styles (Reddy and Knight, 2016;Hu et al., 2017;Prabhumoye et al., 2018) or profiles authorships from text (Verhoeven and Daelemans, 2014;Stamatatos et al., 2018) without parallel corpus of stylistic text.
the absence of such a parallel dataset makes it difficult both to systematically learn the textual variation of multiple styles as well as properly evaluate the models.