Application of i-vector in speech and music classification

Abstract

This paper proposes a speech/music classification system based on i-vector. An analysis of two classification methods, namely cosine distance score (CDS) and support vector machine (SVM) is performed. Two session compensation methods, within-class covariance normalization (WCCN) and linear discriminant analysis (LDA) are also discussed. The performance of proposed systems yields better results compared with Gaussian mixture model (GMM) method and modified low energy ratio (MLER) method.