Deep-speare: A joint neural model of poetic language, meter and rhyme
Table 4: Crowdworker accuracy performance.
['[BOLD] Model', '[BOLD] Accuracy']
We see a steady decrease in accuracy (= improvement in model quality) from LM to LM∗∗ to LM∗∗+PM+RM, indicating that each model generates quatrains that are less distinguishable from human-written ones. Based on the suspicion that workers were using rhyme to judge the poems, we tested a second model, LM∗∗+RM, which is the full model without the pentameter component. We found identical accuracy (0.532), confirming our suspicion that crowd workers depend on only rhyme in their judgements. These observations demonstrate that meter is largely ignored by lay persons in poetry evaluation.