Target sample mining with modified activation residual network for speaker verification.
In the domain of speaker verification, Softmax can be used as a backend for multi-classification, but traditional Softmax methods have some limitations that limit performance. During the training phase, Softmax is used for multi-class training, while the speaker verification stage is a binary classi...
Saved in:
| Main Authors: | Ji Chaoqun, Chen Wei, Ye Peng, Wang Zhou, Zhou Shuhang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2025-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0320256 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Speaker Model Clustering to Construct Background Models for Speaker Verification
by: Gökay DİŞKEN, et al.
Published: (2017-01-01) -
SpeakerNet for Cross-lingual Text-Independent Speaker Verification
by: Hafsa HABIB, et al.
Published: (2020-11-01) -
Speaker Identification and Verification Using Convolutional Neural Network CNN
by: Azhar S. Abdulaziz, et al.
Published: (2025-05-01) -
A lightweight speaker verification approach for autonomous vehicles
by: Yousef Salah, et al.
Published: (2024-12-01) -
Tests of robustness of GMM speaker verification in VoIP telephony
by: Piotr Staroniewicz
Published: (2014-01-01)