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Bidirectional Attention for Text-Dependent Speaker Verification [PDF]

Sensors, 2020
Automatic speaker verification provides a flexible and effective way for biometric authentication. Previous deep learning-based methods have demonstrated promising results, whereas a few problems still require better solutions.
Xin Fang, Tian Gao, Liang Zou, Zhenhua Ling   +3 more
doaj   +4 more sources

A Survey on Text-Dependent and Text-Independent Speaker Verification

IEEE Access, 2022
Speaker verification (SV) aims to detect an individual’s identity from his/her voice. SV has been successfully applied in various areas such as access control, remote service customization, financial transactions, etc.
Youzhi Tu, Weiwei Lin, Man-Wai Mak
doaj   +3 more sources

A Simple Distortion-Free Method to Handle Variable Length Sequences for Recurrent Neural Networks in Text Dependent Speaker Verification

Applied Sciences, 2020
Recurrent neural networks (RNNs) can model the time-dependency of time-series data. It has also been widely used in text-dependent speaker verification to extract speaker-and-phrase-discriminant embeddings. As with other neural networks, RNNs are trained
Sung-Hyun Yoon, Ha-Jin Yu
doaj   +3 more sources

Supervector Extraction for Encoding Speaker and Phrase Information with Neural Networks for Text-Dependent Speaker Verification

Applied Sciences, 2019
In this paper, we propose a new differentiable neural network with an alignment mechanism for text-dependent speaker verification. Unlike previous works, we do not extract the embedding of an utterance from the global average pooling of the temporal ...
Victoria Mingote, Antonio Miguel, Alfonso Ortega, Eduardo Lleida   +3 more
doaj   +3 more sources

Reflection of Conditional Independence Structure to Noise Variability for Noise Robust Text Dependent Speaker Verification

IEEE Access, 2022
In the field of speaker verification (SV), the development of noise-robust systems is a challenge for their deployment in real-world environments. Noise variability compensation is a common strategy for increasing the robustness to noise variations.
Sunghyun Yoon
doaj   +1 more source

Pseudo-Phoneme Label Loss for Text-Independent Speaker Verification

Applied Sciences, 2022
Compared with text-independent speaker verification (TI-SV) systems, text-dependent speaker verification (TD-SV) counterparts often have better performance for their efficient utilization of speech content information. On this account, some TI-SV methods
Mengqi Niu, Liang He, Zhihua Fang, Baowei Zhao, Kai Wang   +4 more
doaj   +1 more source

Analysis-Based Optimization of Temporal Dynamic Convolutional Neural Network for Text-Independent Speaker Verification

IEEE Access, 2023
Temporal dynamic convolution neural networks (TDY-CNNs) extract speaker embeddings considering the time-varying characteristics of speech and improve text-independent speaker verification performance.
Seong-Hu Kim, Hyeonuk Nam, Yong-Hwa Park
doaj   +1 more source

On Training Targets and Activation Functions for Deep Representation Learning in Text-Dependent Speaker Verification

Acoustics, 2023
Deep representation learning has gained significant momentum in advancing text-dependent speaker verification (TD-SV) systems. When designing deep neural networks (DNN) for extracting bottleneck (BN) features, the key considerations include training ...
Achintya Kumar Sarkar, Zheng-Hua Tan
doaj   +1 more source

Evaluating the Performance of Speaker Recognition Solutions in E-Commerce Applications

Sensors, 2021
Two important tasks in many e-commerce applications are identity verification of the user accessing the system and determining the level of rights that the user has for accessing and manipulating system’s resources.
Olja Krčadinac, Uroš Šošević, Dušan Starčević   +2 more
doaj   +1 more source

Regularized Within-Class Precision Matrix Based PLDA in Text-Dependent Speaker Verification

Applied Sciences, 2020
In the field of speaker verification, probabilistic linear discriminant analysis (PLDA) is the dominant method for back-end scoring. To estimate the PLDA model, the between-class covariance and within-class precision matrices must be estimated from ...
Sung-Hyun Yoon, Jong-June Jeon, Ha-Jin Yu   +2 more
doaj   +1 more source