Speaker recognition is a task of identifying persons from their voices. Recently, deep
learning has dramatically revolutionized speaker recognition. However, there is lack of …

Recently deep learning has been successfully used in speech recognition, however it has
not been carefully explored and widely accepted for speaker verification. To incorporate …

Like many machine learning tasks, the performance of speaker verification (SV) systems
degrades when training and test data come from very different distributions. What's more …

Recently satisfactory results have been obtained in NIST speaker recognition evaluations.
These results are mainly due to accurate modeling of a very large development dataset …

This book will help readers understand fundamental and advanced statistical models and
deep learning models for robust speaker recognition and domain adaptation. This useful …

In this paper, a new approach for age estimation from speech signals based on i-vectors is
proposed. In this method, each utterance is modeled by its corresponding i-vector. Then, a …

The newly collected Speakers in the Wild (SITW) database was central to a text-independent
speaker recognition challenge held as part of a special session at Interspeech 2016. The …

This paper proposes techniques to improve the performance of i-vector based speaker
verification systems when only short utterances are available. Short-length utterance i …

In the domain of speech recognition many methods have been proposed over time like
Gaussian mixture models (GMM), GMM with universal background model (GMM-UBM …

In this paper we propose a technique of Within-Class Covariance Correction (WCC) for
Linear Discriminant Analysis (LDA) in Speaker Recognition to perform an unsupervised …