ResearchTrend.AI
  • Papers
  • Communities
  • Organizations
  • Events
  • Blog
  • Pricing
  • Feedback
  • Contact Sales
Papers
Communities
Social Events
Terms and Conditions
Pricing
Contact Sales
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1806.11170
130
9
v1v2v3v4v5 (latest)

GenerationMania: Learning to Semantically Choreograph

28 June 2018
Zhiyu Lin
Kyle Xiao
Mark O. Riedl
ArXiv (abs)PDFHTML
Abstract

Beatmania is a rhythm action game where players play the role of a DJ that performs music by pressing specific controller buttons to mix "Keysounds" (audio samples) at the correct time, unlike other rhythm action games such as Dance Dance Revolution. It has an active amateur Chart (Game stage) creation community, though chart authoring is considered a difficult and time consuming task. We present a deep neural network based process for automatically generating Beatmania charts for arbitrary pieces of music. Given a raw audio track of a song, we identify notes according to instrument, and use a neural network to classify each note as playable or non-playable. The final chart is produced by mapping playable notes to controls. We achieve a high level of performance, beating LSTM baselines.

View on arXiv
Comments on this paper