Music Corpus

Music corpora are organized collections of musical data used for research and analysis, encompassing diverse formats like MIDI files, audio recordings, and symbolic notations. Current research focuses on developing robust algorithms for tasks such as pitch spelling, key detection, and feature extraction from audio, often employing machine learning techniques like variational autoencoders and dynamic programming. These corpora facilitate the study of musical styles across cultures and genres, enabling deeper understanding of musical structure, cognition, and performance, and informing applications like music recommendation systems and music information retrieval. The availability of well-annotated corpora is crucial for advancing music informatics research.