“Public Acceptance” Rating Model of Classical Music

“Public Acceptance” Rating Model of Classical Music

A large proportion of classical music is overlooked by the general public but has the potential to become widely accepted. This paper proposes a model to rate the “public acceptance” score, ranging from 0 to 100, of an arbitrary music piece. It serves as an objective, convenient, and effective way of musical analysis. The model involves a standard dataset for comparison, a preprocessing module, a feature extractor, and a rating module. The standard dataset consists of music pieces that have already gained “public acceptance” according to statistics, while the resampling and normalization module preprocesses the audio, and the feature extractor uses pre-trained VGGish to extract vector features of the audio. Then, these features are compared with those in the standard dataset, and the final rating is calculated. In addition, the model has features that make the rating explainable, and it has been proven by objective and subjective evaluation that this model is accurate and reliable, with the ratings on the same piece highly converged and close to that of manual rating. Possible improvements to this model are marked in the end.