Paper: Learning to Freestyle: Hip Hop Challenge-Response Induction via Transduction Rule Segmentation

ACL ID D13-1011
Title Learning to Freestyle: Hip Hop Challenge-Response Induction via Transduction Rule Segmentation
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2013
Authors

We present a novel model, Freestyle, that learns to improvise rhyming and fluent re- sponses upon being challenged with a line of hip hop lyrics, by combining both bottom- up token based rule induction and top-down rule segmentation strategies to learn a stochas- tic transduction grammar that simultaneously learns both phrasing and rhyming associations. In this attack on the woefully under-explored natural language genre of music lyrics, we exploit a strictly unsupervised transduction grammar induction approach. Our task is par- ticularly ambitious in that no use of any a pri- ori linguistic or phonetic information is al- lowed, even though the domain of hip hop lyrics is particularly noisy and unstructured. We evaluate the performance of the learned model against a model learned only usin...