Rhythmic Pattern

Rhythmic pattern research focuses on understanding and modeling the generation, perception, and manipulation of rhythmic structures across diverse domains, from music and speech to robotics and healthcare. Current research employs various machine learning models, including transformers, recurrent neural networks, and spiking neural networks, often incorporating bio-inspired architectures like central pattern generators to achieve realistic and adaptable rhythmic outputs. This work has implications for music generation and analysis, human-computer interaction, robotics control, and even medical applications like atrial fibrillation detection, highlighting the broad applicability of rhythmic pattern understanding.