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

Speaker recognition has emerged as an important field over the past several decades and
has evolved over time. This work is attempted to investigate speaker verification (SV) …

In this paper, we are interested in exploring Deep Neural Network (DNN) based speaker
embedding for Random-digit task using content information. To this end, a technique is …

Over the past 10 years, digitization, big data, and technology advancement has had a
significant impact on the work done by computer scientists, information scientists, and …

This paper explores novel ideas in building end-to-end deep neural network (DNN) based
text-dependent speaker verification (SV) system. The baseline approach consists of …

Text-dependent speaker verification is becoming popular in the speaker recognition society.
However, the conventional i-vector framework which has been successful for speaker …

This paper introduces a novel approach for extracting speaker embeddings from audio
mixtures of multiple overlapping voices. This approach is based on a multi-task neural …

This paper describes SIIP (Speaker Identification Integrated Project) a high performance
innovative and sustainable Speaker Identification (SID) solution, running over large voice …

Subspace based techniques, such as i-vector and Joint Factor Analysis (JFA) have shown to
provide state-of-the-art performance for fixed phrase based text-dependent speaker …

To adapt the speaker verification (SV) system to a target domain with limited data, this paper
investigates the transfer learning of the model pre-trained on the source domain data. To …