Overview of speaker modeling and its applications: From the lens of deep speaker representation learning
Speaker individuality information is among the most critical elements within speech signals.
By thoroughly and accurately modeling this information, it can be utilized in various …
By thoroughly and accurately modeling this information, it can be utilized in various …
Discriminative neural embedding learning for short-duration text-independent speaker verification
Short duration text-independent speaker verification remains a hot research topic in recent
years, and deep neural network based embeddings have shown impressive results in such …
years, and deep neural network based embeddings have shown impressive results in such …
Re-examining the robustness of voice features in predicting depression: Compared with baseline of confounders
A large proportion of Depression Disorder patients do not receive an effective diagnosis,
which makes it necessary to find a more objective assessment to facilitate a more rapid and …
which makes it necessary to find a more objective assessment to facilitate a more rapid and …
Development of security systems using DNN and i & x-vector classifiers
O Mamyrbayev, A Kydyrbekova, K Alimhan… - 2021 - dspace.enu.kz
The widespread use of biometric systems entails increased interest from cybercriminals
aimed at developing attacks to crack them. Thus, the development of biometric identification …
aimed at developing attacks to crack them. Thus, the development of biometric identification …
Deep neural network based i-vector mapping for speaker verification using short utterances
Text-independent speaker recognition using short utterances is a highly challenging task
due to the large variation and content mismatch between short utterances. I-vector and …
due to the large variation and content mismatch between short utterances. I-vector and …
Exploring the use of an unsupervised autoregressive model as a shared encoder for text-dependent speaker verification
In this paper, we propose a novel way of addressing text-dependent automatic speaker
verification (TD-ASV) by using a shared-encoder with task-specific decoders. An …
verification (TD-ASV) by using a shared-encoder with task-specific decoders. An …
Deep discriminant analysis for i-vector based robust speaker recognition
Linear Discriminant Analysis (LDA) has been used as a standard post-processing procedure
in many state-of-the-art speaker recognition tasks. Through maximizing the inter-speaker …
in many state-of-the-art speaker recognition tasks. Through maximizing the inter-speaker …
Variable frame rate-based data augmentation to handle speaking-style variability for automatic speaker verification
The effects of speaking-style variability on automatic speaker verification were investigated
using the UCLA Speaker Variability database which comprises multiple speaking styles per …
using the UCLA Speaker Variability database which comprises multiple speaking styles per …
[PDF][PDF] Artificial Bandwidth Extension with Memory Inclusion Using Semi-supervised Stacked Auto-encoders.
Artificial bandwidth extension (ABE) algorithms have been developed to improve quality
when wideband devices receive speech signals from narrowband devices or infrastructure …
when wideband devices receive speech signals from narrowband devices or infrastructure …
Data augmentation with moment-matching networks for i-vector based speaker verification
This paper proposes an i-vector generation scheme with conditional generative moment-
matching networks (MMNs) for speaker verification. In this scheme, multiple i-vectors for …
matching networks (MMNs) for speaker verification. In this scheme, multiple i-vectors for …