Chord Annotation

Chord annotation, the process of identifying and labeling chords within musical audio or symbolic scores, is crucial for various music information retrieval (MIR) tasks and music analysis. Current research focuses on improving the accuracy and efficiency of chord annotation using deep learning models, such as conformers and LSTMs, often incorporating techniques like chroma histograms and graph neural networks to represent and process musical data more effectively. These advancements enable more robust chord alignment with audio, facilitate the creation of larger and more diverse datasets, and enhance applications ranging from automated music generation to music education. The resulting improvements in chord recognition and analysis have significant implications for both scientific understanding of music and practical applications in music technology.