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Beat-Aligned Spectrogram-to-Sequence Generation of Rhythm-Game Charts

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arxiv 2311.13687 v1 pith:TGSDT2LT submitted 2023-11-22 cs.LG cs.MMcs.SDeess.AS

Beat-Aligned Spectrogram-to-Sequence Generation of Rhythm-Game Charts

classification cs.LG cs.MMcs.SDeess.AS
keywords generationchartsdatasetfoundgameslargeplayerstraining
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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In the heart of "rhythm games" - games where players must perform actions in sync with a piece of music - are "charts", the directives to be given to players. We newly formulate chart generation as a sequence generation task and train a Transformer using a large dataset. We also introduce tempo-informed preprocessing and training procedures, some of which are suggested to be integral for a successful training. Our model is found to outperform the baselines on a large dataset, and is also found to benefit from pretraining and finetuning.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. ITGPT: A Transformer Based Architecture for the Generation of Dance Dance Revolution and In the Groove Charts

    cs.SD 2026-07 conditional novelty 6.0

    ITGPT, a transformer pipeline, generates DDR/ITG arrow charts from audio with better accuracy and roughly 7x lower generation time than the prior ConvLSTM approach.