Target sample mining with modified activation residual network for speaker verification.

ABSTRACT: 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 classification validation, leading to a discrepancy between the multi-class training in the training phase and the binary classification validation in the verification stage. It is also important to notice the issue of the disparity in the number of positive and negative samples in the sampling process of a binary classification problem. The difference in positive and negative samples can lead to the dominance of negative sample gradients during machine learning training, which can affect the performa

SUBMITTER: Chaoqun J 

PROVIDER: S-EPMC12002510 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature