Meta-analyses of research on consensus estimation have identified an asymmetry in the error patterns between majorities and minorities (Gross & Miller, 1997; Mullen & Hu, 1988). Members of the majority slightly underestimate the size of their own group, whereas members of the minority strongly overestimate the size of theirs. The present analysis shows that a single psychological assumption abo...

Voice biometrics for user authentication is a task in which the object is to perform convenient, robust and secure authentication of speakers. In this work we investigate the use of state-of-the-art text-independent and text-dependent speaker verification technology for user authentication. We evaluate four different authentication conditions: speaker specific digit stings, global digit strings...

AbstractAiming at complexity and uncertainty of actual decision-making environment, this study proposes a multiple attribute decision-making model of grey target based on positive and negative bull’s-eye. Firstly, it defines that the optimal effect vector and the worst effect vector of grey target decision are respectively positive, negative bull’s-eye of the grey target; secondly, comprehensiv...

This paper investigates the effects of limited speech data in the context of speaker verification using the Gaussian mixture model (GMM) mean supervector support vector machine (SVM) classifier. This classifier provides state-of-the-art performance when sufficient speech is available, however, its robustness to the effects of limited speech resources has not yet been ascertained. Verification p...

Nuisance attribute projection (NAP) and within-class covariance normalization (WCCN) are two effective techniques for intersession variability compensation in SVM based speaker verification systems. However, by normalizing or removing the nuisance subspace containing the session variability can not guarantee to enlarge the distance between speakers. In this paper, we investigated the probabilit...

A kind of multi-attribute grey-target decision model based on positive-negative target center is put forward aimed at the complexity and uncertainty of the actual decision environment. Firstly, the optimal effect vector and the worst effect vector of the grey-target decision are respectively defined as the positive and negative clouts; secondly, the spatial projection distance between the posit...

Modern embedding methods focus only on the words in the text. The word or sentence embeddings are trained to represent the semantic meaning of the raw texts. However, many quantified attributes associated with the text, such as numeric attributes associated with Yelp review text, are ignored in the vector representation learning process. Those quantified numeric attributes can provide important...

We have been using a phone-based cepstral system with polynomial features in NIST evaluations for the past two years. This system uses three broad phone classes, three states per class, and third-order polynomial features obtained from MFCC features. In this paper, we present a complete analysis of the system. We start from a simpler system that does not use phones or states and show that the a...