Abstract
Harmony, which plays an important role in enriching melody expression, is a combination of multiple notes. Melody coordination involves adding harmony effect to a single note of melody, which involves professional knowledge of basic music theory and harmony rules, and requires a high technical threshold. Under the macro background of deep learning and neural network technology, artificial intelligence is widely used in music retrieval, music creation, and music teaching. In this article, we provide a powerful tool for piano music creation by manually arranging melody and harmony instead of using deep learning. In this paper, harmonic elimination is divided into three subtasks: note detection, measurement, and multifundamental frequency estimation and model training. The music signal is divided into several segments by note detection, and the main notes and harmonic components of each segment are extracted by multifundamental frequency estimation, which are used as the features and labels of the neural network, so as to give a model with the ability of arrangement and harmony.
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