Drum Transcription

Automatic drum transcription aims to computationally identify and represent drum hits within audio recordings, a crucial task in music information retrieval and analysis. Current research focuses on overcoming limitations in training data by developing large, high-quality datasets of both synthetic and real-world drum recordings, employing deep learning models like convolutional neural networks and generative adversarial networks (GANs) for improved accuracy and real-time performance. These advancements are driving progress in drum source separation and enabling innovative applications such as AI-powered drum transcription robots and VST plugins for drum sound design and manipulation.