Abstract
In order to solve the problem of poor speaker recognition performance on multi-language corpus on convolutional neural networks and large amount of calculations on multiple parameters, this paper draws on asymmetric convolution and center loss (Center Loss) functions to improve and optimize the ResNet model. And perform speaker recognition tasks in the Chinese-Uyghur corpus. The results show that, compared with the original model, the improved model has higher accuracy, fewer parameters, and reduced computational complexity.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have