A review of deep learning techniques for speech processing
The field of speech processing has undergone a transformative shift with the advent of deep
learning. The use of multiple processing layers has enabled the creation of models capable …
learning. The use of multiple processing layers has enabled the creation of models capable …
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 …
A survey of speaker recognition: Fundamental theories, recognition methods and opportunities
Humans can identify a speaker by listening to their voice, over the telephone, or on any
digital devices. Acquiring this congenital human competency, authentication technologies …
digital devices. Acquiring this congenital human competency, authentication technologies …
The ins and outs of speaker recognition: lessons from VoxSRC 2020
The VoxCeleb Speaker Recognition Challenge (VoxSRC) at Interspeech 2020 offers a
challenging evaluation for speaker recognition systems, which includes celebrities playing …
challenging evaluation for speaker recognition systems, which includes celebrities playing …
Deep speaker recognition: Process, progress, and challenges
Speaker recognition is related to human biometrics dealing with the identification of
speakers from their speech. Speaker recognition is an active research area and being …
speakers from their speech. Speaker recognition is an active research area and being …
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 …
Improved meta learning for low resource speech recognition
We propose a new meta learning based framework for low resource speech recognition that
improves the previous model agnostic meta learning (MAML) approach. The MAML is a …
improves the previous model agnostic meta learning (MAML) approach. The MAML is a …
RawNeXt: Speaker verification system for variable-duration utterances with deep layer aggregation and extended dynamic scaling policies
Despite achieving satisfactory performance in speaker verification using deep neural
networks, variable-duration utterances remain a challenge that threatens the robustness of …
networks, variable-duration utterances remain a challenge that threatens the robustness of …
End-to-end speaker verification via curriculum bipartite ranking weighted binary cross-entropy
End-to-end speaker verification achieves the verification through estimating directly the
similarity score between a pair of utterances, which is formulated as a binary (ie, target …
similarity score between a pair of utterances, which is formulated as a binary (ie, target …
Improved end-to-end dysarthric speech recognition via meta-learning based model re-initialization
Dysarthric speech recognition is a challenging task as dysarthric data is limited and its
acoustics deviate significantly from normal speech. Model-based speaker adaptation is a …
acoustics deviate significantly from normal speech. Model-based speaker adaptation is a …