Bob is a free signal processing and machine learning toolbox originally developed by the
Biometrics group at Idiap Research Institute, Switzerland. The toolbox is designed to meet the …

This paper details the submission from the Speech and Audio Research Lab of Queensland
University of Technology (QUT) to the inaugural 2006 NIST Spoken Term Detection …

This paper applies inter-session variability modelling and joint factor analysis to face
authentication using Gaussian mixture models. These techniques, originally developed for speaker …

In this paper, we present a scalable and exact solution for probabilistic linear discriminant
analysis (PLDA). PLDA is a probabilistic model that has been shown to provide state-of-the-art …

This study examines session variability modelling for face authentication using Gaussian
mixture models. Session variability modelling aims to explicitly model and suppress detrimental …

In this paper we introduce the facereclib, the first software library that allows to compare a
variety of face recognition algorithms on most of the known facial image databases and that …

This paper applies score and feature normalization techniques to parts-based Gaussian mixture
model (GMM) face authentication. In particular, we propose to utilize techniques that are …

An evaluation of the verification and calibration performance of a face recognition system
based on inter‐session variability modelling is presented. As an extension to calibration …

While spoken term detection (STD) systems based on word indices provide good accuracy,
there are several practical applications where it is infeasible or too costly to employ an …

This paper introduces a novel technique to directly optimise the Figure of Merit (FOM) for
phonetic spoken term detection. The FOM is a popular measure of STD accuracy, making it an …