ABSTRACT
In the previous chapter, we have shown that personalization is an effective way to deal with the subjectivity issue of MER. In this chapter, we move on to discuss more advanced methods that are useful for addressing the subjectivity issue, including the bag-of-users model and the residual modeling. Based on these two methods, a two-layer personalization scheme is developed. A first-layer regressor is trained to predict the general perception of a music piece, and a second-layer regressor is trained to predict the difference between the general perception and a user’s individual perception. This two-layer personalization scheme is more effective than the single-layer one (that is, personalized MER) because the music content and the individuality of the user are treated separately.
