Speaker recognition based on deep learning: An overview
Speaker recognition is a task of identifying persons from their voices. Recently, deep
learning has dramatically revolutionized speaker recognition. However, there is lack of …
learning has dramatically revolutionized speaker recognition. However, there is lack of …
Self-supervised speaker embeddings
Contrary to i-vectors, speaker embeddings such as x-vectors are incapable of leveraging
unlabelled utterances, due to the classification loss over training speakers. In this paper, we …
unlabelled utterances, due to the classification loss over training speakers. In this paper, we …
Few shot speaker recognition using deep neural networks
The recent advances in deep learning are mostly driven by availability of large amount of
training data. However, availability of such data is not always possible for specific tasks such …
training data. However, availability of such data is not always possible for specific tasks 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 …
Speaker verification using attentive multi-scale convolutional recurrent network
Y Li, Z Jiang, W Cao, Q Huang - Applied Soft Computing, 2022 - Elsevier
In this paper, we propose a speaker verification method by an Attentive Multi-scale
Convolutional Recurrent Network (AMCRN). The proposed AMCRN can acquire both local …
Convolutional Recurrent Network (AMCRN). The proposed AMCRN can acquire both local …
Deep learning for speaker recognition: A comparative analysis of 1D-CNN and LSTM models using diverse datasets
Speaker recognition is a vital component of identity verification and security systems that has
made significant progress through the use of deep neural networks. This article examines …
made significant progress through the use of deep neural networks. This article examines …
CoughMatch–subject verification using cough for personal passive health monitoring
Automatic cough detection using audio has advanced passive health monitoring on devices
such as smart phones and wearables; it enables capturing longitudinal health data by …
such as smart phones and wearables; it enables capturing longitudinal health data by …
Predicting concrete's strength by machine learning: Balance between accuracy and complexity of algorithms
The properties of concretes are controlled by the rate of reaction of their precursors, the
chemical composition of the binding phase (s), and their structure at different scales …
chemical composition of the binding phase (s), and their structure at different scales …
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 …
Quality measures for speaker verification with short utterances
The performances of the automatic speaker verification (ASV) systems degrade due to the
reduction in the amount of speech used for enrollment and verification. Combining multiple …
reduction in the amount of speech used for enrollment and verification. Combining multiple …