Automatic Genre Classification of TV Programmes Using Gaussian Mixture Models and Neural Networks

Abstract

In this paper we investigate the problem of automatically identifying the genre of TV programmes. The approach here proposed is based on two foundations: Gaussian mixture models (GMMs) and artificial neural networks (ANNs). Firstly, we use Gaussian mixtures to model the probability distributions of low-level audiovisual features. Secondly, we use the parameters of each mixture model as new feature vectors. Finally, we train a multilayer perceptron (MLP), using GMM parameters as input data, to identify seven television programme genres. We evaluated the effectiveness of the proposed approach testing our system on a large set of data, summing up to more than 100 hours of broadcasted programmes.