Gaussian Process Method for Music Genre Sorting and Music Emotion Approximation
Keywords:
Emotion Estimation, Gaussian Processes Model, Genres, Music Information RetrievalAbstract
In the zone of Music Information Retrieval (MIR), music genre classification
and music emotion recognition are the two chief responsibilities. In this
project work, these two tasks are included. Music genre cataloging and
emotion estimation has been proposed using Gaussian Processes (GPs)
which is Bayesian nonparametric models. These GPs used to capture
highly nonlinear data relationships in novelty detection, dimensionality
reduction, classical regression and cataloging tasks and time series
analysis and so on; we explore the suitability of GPs model for music
genre classification and music emotion. Along with this, we are reducing
the time required for feature extraction for classification tasks. In this
we consider only higher order feature extraction
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