Antithesis structure analysis in slogan using span candidate refinement with word correspondence

Abstract

In recent years, slogans, which are sentences that express products and works, have attracted attention due to their importance in marketing. An analysis of the previous slogans has shown that the interesting points of slogans also appear in rhetorical techniques such as metaphor and repetition. Additionally, some experimental results show that slogans with rhetorical techniques improve advertising effects. Therefore, in this study, we focused on slogans that include an antithesis structure, among many rhetorical techniques. More specifically, towards the generation of slogans with antithesis structures, we perform structural analysis using a corpus with antithesis spans annotated. Then, we can extract the knowledge about the structures. Our proposed model introduces end-position detection for each span before antithesis span identification, which enables the model to capture the word correspondences. The proposed model showed better accuracy in a shorter calculation time by refining the span candidates by the end-position detection.