2 citations · 6 across the 7 of their papers we have counts for
7 papers
Data Generation Using Pass-phrase-dependent Deep Auto-encoders for Text-Dependent Speaker Verification
Achintya Kumar Sarkar, Md Sahidullah, Zheng-Hua Tan
In this paper, we propose a novel method that trains pass-phrase specific deep neural network (PP-DNN) based auto-encoders for creating augmented data for text-dependent speaker ve…
UIAI System for Short-Duration Speaker Verification Challenge 2020
Md Sahidullah, Achintya Kumar Sarkar, Ville Vestman +5
In this work, we present the system description of the UIAI entry for the short-duration speaker verification (SdSV) challenge 2020. Our focus is on Task 1 dedicated to text-depend…
Data augmentation enhanced speaker enrollment for text-dependent speaker verification
Achintya Kumar Sarkar, Himangshu Sarma, Priyanka Dwivedi +1
Data augmentation is commonly used for generating additional data from the available training data to achieve a robust estimation of the parameters of complex models like the one f…
On Bottleneck Features for Text-Dependent Speaker Verification Using X-vectors
Achintya Kumar Sarkar, Zheng-Hua Tan
Applying x-vectors for speaker verification has recently attracted great interest, with the focus being on text-independent speaker verification. In this paper, we study x-vectors…
Time-Contrastive Learning Based DNN Bottleneck Features for Text-Dependent Speaker Verification
Achintya Kr. Sarkar, Zheng-Hua Tan
In this paper, we present a time-contrastive learning (TCL) based bottleneck (BN)feature extraction method for speech signals with an application to text-dependent (TD) speaker ver…
Incorporating Pass-Phrase Dependent Background Models for Text-Dependent Speaker Verification
A. K. Sarkar, Zheng-Hua Tan
In this paper, we propose pass-phrase dependent background models (PBMs) for text-dependent (TD) speaker verification (SV) to integrate the pass-phrase identification process into…