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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 …
AI-assisted enhancement of student presentation skills: Challenges and opportunities
J Chen, P Lai, A Chan, V Man, CH Chan - Sustainability, 2023 - mdpi.com
Oral presentation is a popular type of assessment in undergraduate degree programs.
However, presentation delivery and grading pose considerable challenges to students and …
However, presentation delivery and grading pose considerable challenges to students and …
ASV-Subtools: Open source toolkit for automatic speaker verification
In this paper, we introduce a new open source toolkit for automatic speaker verification
(ASV), named ASV-Subtools. Adopting PyTorch as main deep learning engine and Kaldi …
(ASV), named ASV-Subtools. Adopting PyTorch as main deep learning engine and Kaldi …
Robust channel learning for large-scale radio speaker verification
Recent research in speaker verification has increasingly focused on achieving robust and
reliable recognition under challenging channel conditions and noisy environments …
reliable recognition under challenging channel conditions and noisy environments …
Robust cross-domain speaker verification with multi-level domain adapters
Speaker verification encounters significant challenges when confronted with diverse domain
data, often resulting in performance degradation due to domain mismatch. To enhance …
data, often resulting in performance degradation due to domain mismatch. To enhance …
Generalized domain adaptation framework for parametric back-end in speaker recognition
State-of-the-art speaker recognition systems comprise a speaker embedding front-end
followed by a probabilistic linear discriminant analysis (PLDA) back-end. The effectiveness …
followed by a probabilistic linear discriminant analysis (PLDA) back-end. The effectiveness …
Barlow twins self-supervised learning for robust speaker recognition
Acoustic noise is a big challenge for speaker recognition systems. The state-of-the-art
speaker recognition systems are based on deep neural network speaker embeddings called …
speaker recognition systems are based on deep neural network speaker embeddings called …
Unsupervised adaptive speaker recognition by coupling-regularized optimal transport
Cross-domain speaker recognition (SR) can be improved by unsupervised domain
adaptation (UDA) algorithms. UDA algorithms often reduce domain mismatch at the cost of …
adaptation (UDA) algorithms. UDA algorithms often reduce domain mismatch at the cost of …
Learning noise robust ResNet-based speaker embedding for speaker recognition
The presence of background noise and reverberation, especially in far distance speech
utterances diminishes the performance of speaker recognition systems. This challenge is …
utterances diminishes the performance of speaker recognition systems. This challenge is …
SE/BN Adapter: Parametric Efficient Domain Adaptation for Speaker Recognition
Deploying a well-optimized pre-trained speaker recognition model in a new domain often
leads to a significant decline in performance. While fine-tuning is a commonly employed …
leads to a significant decline in performance. While fine-tuning is a commonly employed …