Speaker Recognition Method Based on Improved Time Delay Neural Network
HU Guichao
Abstract：An improved time delay neural network(TDNN)speaker recognition method is proposed to improve the accuracy of speaker recognition.Firstly,the features of audio are trained through TDNN network to obtain the feature expression of some speakers.Then it is processed simultaneously by the added quantization and counting operators(QCO).QCO can make full use of the low-level texture features of audio to obtain the detailed information of features.The experimental results show that the improved time-delay neural network can obtain more information from network training in a relatively small amount of data,it has obvious ad-vantages in the network with a small number of training sets.When the amount of data is further increased,the effect is more obvi-ous.The training adds the texture statistical method to extract the detailed features of the structure,which makes the speaker recog-nition performance better.
Keywords：speaker recognitiondelay neural networksquantization and counting operatorsqco-vector
Publication Date：2023-12-20
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 2827-2830 )