摘要
Abstract
Voiceprint recognition belongs to a new type of biological recognition technology,the combination of comprehen-sive research on life science,computer technology and other technology.With the development of deep learning technology constant-ly,voiceprint recognition technology in case detection,the application of intelligent snatched,payment system is also more and more,this article in view of the existing recognition rate is low,voiceprint recognition system identification efficiency is slow.An im-proved DenseNet network model based on attentional mechanism is proposed as an acoustic model to further improve the perfor-mance of the voice print recognition system.Firstly,the speech is preprocessed and extracted into the improved DenseNet network,and finally into the SoftMax function to output the results.Finally,the results are verified and compared by multiple groups of experi-ments.The experimental results show that,compared with other traditional acoustic models,the accuracy and AUC of DenseNet net-work improved by attention mechanism are improved by 4.25%and 4.18%respectively,and the equal error rate is reduced by 6.09%,which proves the rationality of the model for the voice print recognition task.关键词
注意力机制/声纹识别/DenseNet/声学模型Key words
attention mechanism/voiceprint recognition/DenseNet/acoustic model分类
信息技术与安全科学
