In this paper we investigate two discriminative classification approaches for frame-based speaker identification and verification, namely Support Vector Machine (SVM) and Sparse Kernel Logistic Regression (SKLR). SVMs have already shown good results in regression and classification in several fields of pattern recognition as well as in continuous speech recognition. While the non-probabilistic ...

Gaussian Mixture Models (GMMs) in combination with Support Vector Machine (SVM) classifiers have been shown to give excellent classification accuracy in speaker recognition. In this work we use this approach for language identification, and we compare its performance with the standard approach based on GMMs. In the GMM-SVM framework, a GMM is trained for each training or test utterance. Since i...

To overcome the defects of common used algorithms based on model for abnormal speech recognition, which existed insufficient training data and difficult to fit each type of abnormal characters, an abnormal speech detection method based on GMM-UBM was proposed in this paper. For compensating the defects of methods based on model which difficult to deal with the diversification speech. Firstly, m...

The contribution of this paper is to analyse the role of network interdependencies in a dynamic panel data model for German internal migration fl ows since re-unifi cation. So far, a capacious account of spatial patterns in German migration data is still missing in the empirical literature. In the context of this paper, network dependencies are associated with correlations of migration fl ows s...

In this paper we present an empirical analysis of the residential demand for electricity using annual aggregate data at the state level for 48 US states from 1995 to 2007. Earlier literature has examined residential energy consumption at the state level using annual or monthly data, focusing on the variation in price elasticities of demand across states or regions, but has failed to recognize o...

JEL Classification G32, G34, G39. This paper examines the role of debt resulting from bank financing for corporate governance towards the activities of withdrawing cash and assets to controlling shareholders’ account to benefit their rights by capturing secondary data for 250 nonfinancial firms listed in the Vietnam Index, considered as one of the emerging stock markets, during the period from ...

This paper describes the derivation of a sequence kernel that transforms speech utterances into probabilistic vectors for classification in an expanded feature space. The sequence kernel is built upon a set of Gaussian basis functions, where half of the basis functions contain speaker specific information while the other half implicates the common characteristics of the competing background spe...