Voice Print Recognition Check-in System Based on Resnet

Abstract

With the development of modern technology and the rise of artificial intelligence, the application scenarios of identity authentication technology are becoming more and more complex, especially the current situation of the spread of the novel coronavirus, the traditional identity authentication technology can no longer meet people's actual needs, and the society urgently needs a secure and convenient identity authentication technology. Voice print recognition technology is an identity recognition method that uses specific feature extraction methods to extract the features that can identify the speaker's identity from the original speech input, and then uses these features to identify the speaker's identity. Aiming at the above problems, this paper proposes a deep learning-based voicing recognition algorithm, which is based on the theoretical knowledge of deep learning. The research work includes the following aspects: providing convolutional network to extract features; The "speech feature template library" is established by massive training. Research on matching and recognition algorithm; Research on check-in system based on voice print recognition. Based on this algorithm, this paper designs and implements a voiceprint recognition check-in system with clear interactive interface. The system has the functions of adding members, refreshing the voice library, checking in with the voice print, clearing the results and so on. The system interface will display the data of the voice print library and the historical check-in record, as well as the current recognition results, accuracy and check-in time. The average recognition rate of the system is about 95%, which can meet the requirement of practical application.