GP Model based Music Genre Classification and Music Emotion Estimation

Ms. Pranali L. Kakad, Dr.Varsha H. Patil


In the area of Music Information Retrieval (MIR),
music genre classification and music emotion recognition are
the two main tasks. In this project work, these two tasks
are genre classification and emotion estimation
has been praposed using Gaussian Processes (GPs) which is
Bayesian nonparametric models.This GPs used to capture highly
nonlinear data relationships in novelty detection,dimensionality
reduction,classical regression and classification 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

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