Rhythm Game

Rhythm games, which require players to synchronize actions with music, are a rich area of research focusing on automated chart generation, music-driven motion synthesis, and the analysis of musical features like beat and rhythm. Current research employs various deep learning architectures, including Transformers, LSTMs, and convolutional neural networks, to model and generate musical sequences, analyze lyrical content for bias, and even decode musical information from brain activity. This work has implications for music composition, dance generation, and the broader understanding of human perception and interaction with music, as well as for improving the accessibility and creation of rhythm games themselves.