Bostjan Vesnicer

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The paper introduces a feature extraction technique for face recognition called the phase-based Gabor Fisher classifier (PBGFC). The PBGFC method constructs an augmented feature vector which encompasses Gabor-phase information derived from a novel representation of face images - the oriented Gabor phase congruency image (OGPCI) - and then applies linear(More)
The paper presents our efforts in the Gender Sub-Challenge and the Affect Sub-Challenge of the INTERSPEECH 2010 Paralinguistic Challenge. The system for the Gender Sub-Challenge is based on modeling the Mel-Frequency Cepstrum Coefficients using Gaussian mixture models, building a separate model for each of the gender categories. For the Affect Sub-Challenge(More)
This paper evaluates the performance of the twelve primary systems submitted to the evaluation on speaker verification in the context of a mobile environment using the MOBIO database. The mobile environment provides a challenging and realistic test-bed for current state-of-the-art speaker verification techniques. Results in terms of equal error rate (EER),(More)
We propose a way of integrating likelihood ratio (LR) decision criterion with nuisance attribute projection (NAP) for Gaussian mixture model(GMM-) based speaker verification. The experiments on the core test of the NIST speaker recognition evaluation (SRE) 2005 data show that the performance of the proposed approach is comparable to that of the standard(More)
Illumination induced appearance changes represent one of the open challenges in automated face recognition systems still significantly influencing their performance. Several techniques have been presented in the literature to cope with this problem; however, a universal solution remains to be found. In this paper we present a novel normalization scheme(More)
Face recognition in uncontrolled environments remains an open problem that has not been satisfactorily solved by existing recognition techniques. In this paper, we tackle this problem using a variant of the recently proposed Probabilistic Linear Discriminant Analysis (PLDA). We show that simplified versions of the PLDA model, which(More)
Most of the existing literature on i-vector-based speaker recognition focuses on recognition problems, where i-vectors are extracted from speech recordings of sufficient length. The majority of modeling/recognition techniques therefore simply ignores the fact that the i-vectors are most likely estimated unreliably when short recordings are used for their(More)
A system for speaker-based audio-indexing and an application for speaker-tracking in broadcast news audio are presented. The process of producing an indexing information in continuous audio streams based on detected speakers is composed of several tasks and is therefore treated as a multistage process. The main building blocks of such an indexing system(More)