Using Machine Translation to Convert Between Difficulties in Rhythm Games

Authors

  • Kevin Gold Rochester Institute of Technology
  • Alex Olivier Wellesley College

Keywords:

machine translation, game content, bigram model, rhythm game, difficulty, music

Abstract

A method is presented for converting between Guitar Hero difficulty levels by treating the problem as one of machine translation, with the different difficulties as different languages. The Guitar Hero I and II discs provide aligned corpora with which to train bigram-based language models and translation models. Given an Expert sequence, the model can create sequences of Hard, Medium, or Easy difficulty that retain the feel of the original, while obeying heuristics typical of those difficulties. Training the model requires a single pass through the corpus, while translation is quadratic in the length of the Expert sequence. The method outperforms a recurrent neural network in producing sequences that match the hand-designed levels. The method may make it easier for amateurs to produce content for the Rock Band Network.

Downloads

Published

2010-10-10

How to Cite

Gold, K., & Olivier, A. (2010). Using Machine Translation to Convert Between Difficulties in Rhythm Games. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 6(1), 27-32. Retrieved from https://ojs.aaai.org/index.php/AIIDE/article/view/12396