Deep rapping: Character level neural models for automated rap lyrics composition

Abstract

“Dope”, “Twerk”, “YOLO”, these are just some of the words that originated from rap music which made into the Oxford dictionary. Rap lyrics break the traditional structure of English, making use of shorten and invented words to create rhythmic lines and inject informality, humor, and attitude in the music. In this paper, we attack this domain on a computational perspective, by implementing deep learning models that could forge rap lyrics through unsupervised character prediction. Our work employed novel recurrent neural networks for the task at hand and showed that these can emulate human creativity in rap lyrics composition based on qualitative analysis, rhyme density score, and Turing test performed on computer science students.