Characteristics Study of Dance-charts on Rhythm-based Video Games

Tsujino, Yudai; Yamanishi, Ryosuke; Yamashita, Yoichi

doi:10.1109/cig.2019.8848126

Cited by 4 publications

(2 citation statements)

References 5 publications

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“…Halina and Guzdial [2021] transferred this general approach to another rhythm game, Taiko no Tatsujin. Tsujino et al [2019] first investigated the task of level difficulty analysis or difficulty estimation of StepMania levels. They clustered levels based on automatically extracted handpicked features and found the resulting clusters to correlate with difficulty levels.…”

Section: Related Workmentioning

confidence: 99%

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Ordinal Regression for Difficulty Estimation of StepMania Levels

Franks¹,

Dinkelmann²,

Fellenz³

et al. 2023

Preprint

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StepMania is a popular open-source clone of a rhythm-based video game. As is common in popular games, there is a large number of communitydesigned levels. It is often difficult for players and level authors to determine the difficulty level of such community contributions. In this work, we formalize and analyze the difficulty prediction task on StepMania levels as an ordinal regression (OR) task. We standardize a more extensive and diverse selection of this data resulting in five data sets, two of which are extensions of previous work. We evaluate many competitive OR and non-OR models, demonstrating that neural network-based models significantly outperform the state of the art and that StepMania-level data makes for an excellent test bed for deep OR models. We conclude with a user experiment showing our trained models' superiority over human labeling.

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Section: Related Workmentioning

confidence: 99%

“…StepMania-level creators and players. So far, only level generation [Donahue et al, 2017;Tsujino and Yamanishi, 2018], and difficulty prediction [Tsujino et al, 2019;Caronongan and Marcos, 2021] have been applied to this data. However, other tasks or subtasks of the former utilizing this data may also be interesting.…”

Section: Introductionmentioning

confidence: 99%