Due to the widespread deployment of fingerprint/face/speaker recognition systems, risk in these especially adversarial attack, has drawn increasing attention recent years. Previous researches mainly studied attack vision-based such as fingerprint and face recognition. While for speech-based systems not been well yet, although it widely used our daily life. In this article, we attempt fool state...

Speaker recognition achieved great progress recently, however, it is not easy or efficient to further improve its performance via traditional solutions: collecting more data and designing new neural networks. Aiming at the fundamental challenge of speech data, i.e. low information density, multimodal learning can mitigate this by introducing richer discriminative as input for identity recogniti...

We present a Bayesian formulation for deep speaker embedding, wherein the xi-vector is counterpart of x-vector, taking into account uncertainty estimate. On technology front, we offer simple and straightforward extension to now widely used x-vector. It consists an auxiliary neural net predicting frame-wise input sequence. show that proposed leads substantial improvement across all operating poi...

Research on speaker recognition is extending to address the vulnerability in wild conditions, among which genre mismatch perhaps most challenging, for instance, enrollment with reading speech while testing conversational or singing audio. This leads complex and composite inter-session variations, both intrinsic (i.e., speaking style, physiological status) extrinsic recording device, background ...

In this paper we briefly describe the BioSec multimodal biometric database and analyze its use in automatic text-dependent speaker recognition research. The paper is structured into four parts: a short introduction to the problem of text-dependent speaker recognition; a brief review of other existing databases, including monomodal text-dependent speaker recognition databases and multimodal biom...

Speaker recognition is usually accomplished by building a set of models from speech of a known speaker, training data, and subsequently using a pattern matching algorithm to score the speech from an unknown speaker, test data. In this paper we discard the notion of train and test data in speaker recognition and introduce the multilateral scoring technique. This technique comprises building spea...