Melody Harmonization

Melody harmonization, the task of automatically generating chord progressions that complement a given melody, is a vibrant area of music information retrieval research. Current efforts focus on improving the quality, variability, and emotional expressiveness of generated harmonies, often employing deep learning models like Variational Autoencoders and Transformers, incorporating techniques such as attention mechanisms and domain adversarial training to enhance controllability and disentangle latent representations. These advancements aim to create more sophisticated and musically expressive harmonization systems, with applications ranging from automated music composition tools to assistive technologies for musicians and composers.