A spoof detection algorithm supports the speaker verification system to examine false claims by an imposter through careful analysis of input test speech. The scores are employed categorize genuine and spoofed samples effectively. Under mismatch conditions, acceptance ratio increases can be reduced appropriate score normalization techniques. In this article, we using normalized Discounted Cumul...

BACKGROUND Identifying key variables such as disorders within the clinical narratives in electronic health records has wide-ranging applications within clinical practice and biomedical research. Previous research has demonstrated reduced performance of disorder named entity recognition (NER) and normalization (or grounding) in clinical narratives than in biomedical publications. In this work, w...

In this work we aim at compensating the degrading effects of utterance length variability of speaker verification systems, which appear in many typical applications such as forensics. The paper concentrates in the score misalignments due to different utterance lengths, proposing several algorithms for its normalization. In order to test the proposed methods, we have built two corpora from NIST ...

conclusions these open-label data show trends toward normalization of eeg and concomitant clinical improvement using magnetic stimulation for ptsd. results of the 21 patients who initiated therapy, 16 completed treatment. clinical improvements on the pcl-m were seen in these 16 patients, with an average pre-treatment score of 54.9 and post-treatment score of 31.8 (p < 0.001). in addition, relat...

In this paper a new text-independent speaker verification method is proposed based on likelihood score normalization and the global speaker model, which is established to represent the universal features of speech and environment, and to normalize the likelihood score. As a result the equal error rates are decreased significantly, verification procedure is accelerated and system adaptability is...

This paper deals with the problematic of speaker variability in a task of pronunciation verification for the speech therapy of children and young adults in Computer-Aided Pronunciation Training (CAPT) tools. The baseline system evaluates two different score normalization techniques: Traditional Test normalization (T-norm), and a novel Nbest based normalization that outperforms the first by norm...

This paper proposes a new approach to unsupervised speaker adaptation inspired by the recent success of the factor analysisbased Total Variability Approach to text-independent speaker verification [1]. This approach effectively represents speaker variability in terms of low-dimensional total factor vectors and, when paired alongside the simplicity of cosine similarity scoring, allows for easy m...

This paper examines a method to normalize a score of a stochastic motif, represented by a hidden Markov model (HMM). The accuracy of the Z score method, which is one of the score normalization method, is compared with that of the whole search method.

This paper addresses the incorporation of quality measures to videobased person authentication. A theoretical framework to incorporate quality measures in biometric authentication is exposed. Two different quality-based score normalization techniques are derived from this theoretical framework. Furthermore, a quality-based frame selection technique and a new face image quality measure are also ...

Most techniques for speaker verification today use Gaussian Mixture Models (GMMs) and make the decision by comparing the likelihood of the speaker model to the likelihood of a universal background model (UBM). The paper proposes to replace the UBM by an individual background model (IBM) that is generated for each speaker. The IBM is created using the K-nearest cohort models and the UBM by a sim...