Automatic Analysis of Rhythmic Poetry with Applications to Generation and Translation
Erica Greene, Tugba Bodrumlu, Kevin K. Knight · 2010
We employ statistical methods to analyze, generate, and translate rhythmic poetry. We first apply unsupervised learning to reveal word-stress patterns in a corpus of raw poetry. We then use these word-stress patterns, in addition to rhyme and discourse models, to generate English love poetry. Finally, we translate Italian poetry into English, choosing target realizations that conform to desired rhythmic patterns. 1